Abstract: We consider the Railway Traveling Salesman Problem. We
show that this problem can be reduced to a variant of the generalized
traveling salesman problem, defined on an undirected graph G = (V,E)
with the nodes partitioned into clusters, which consists in finding a mini
mum cost cycle spanning a subset of nodes with the property that exactly
two nodes are chosen from each cluster. We describe an exact exponen
tial time algorithm for the problem, as well we present two mixed integer
programming models of the problem. Based on one of this models pro
posed, we present an efficient solution procedure based on a cutting plane
algorithm. Extensive computational results for instances taken from the
railroad company of the Netherlands Nederlandse Spoorwegen and involv
ing graphs with up to 2182 nodes and 38650 edges are reported.
Abstract: Paul Spirakis is an eminent, talented, and influential researcher that contributed significantly to computer science. This article is a modest attempt of a biographical sketch of Paul, which we drafted with extreme love and honor.
Abstract: In mobile adhoc networks (MANETs), the mobility of the nodes is a complicating factor that significantly affects the effectiveness and performance of the routing protocols. Our work builds upon recent results on the effect of node mobility on the performance of available routing strategies (i.e.~path based, using support) and proposes a protocol framework that exploits the usually different mobility rates of the nodes by adapting the routing strategy during execution. We introduce a metric for the relative mobility of the nodes, according to which the nodes are classified into mobility classes. These mobility classes determine, for any pair of an origin and destination, the routing technique that best corresponds to their mobility properties. Moreover, special care is taken for nodes remaining almost stationary or moving with high (relative) speeds. Our key design goal is to limit the necessary implementation changes required to incorporate existing routing protocols in to our framework. We provide extensive evaluation of the proposed framework, using a wellknown simulator (NS2). Our first findings demonstrate that the proposed framework improves, in certain cases, the performance of the existing routing protocols.
Abstract: In adhoc mobile networks (MANET), the mobility of the nodes is a complicating factor that significantly affects the effectiveness and performance of the routing protocols. Our work builds upon the recent results on the effect of node mobility on the performance of available routing strategies (i.e.~path based, using support) and proposes a protocol framework that exploits the usually different mobility rates of the nodes by adopting the routing strategy during execution. We introduce a metric for the relative mobility of the nodes, according to which the nodes are classified into mobility classes. These mobility classes determine, for any pair of origin and destination, the routing technique that best corresponds to their mobility properties. Moreover, special care is taken for nodes remaining almost stationary or moving with high (relative) speeds. Our key design goal is to limit the necessery implementation changes required to incorporate existing routing protocols in our framework. We provide extensive evaluation of the proposed framework, using a wellknown simulator (NS2). Our first findings demonstrate that the proposed framework improves, in certain cases, the performance of the existing routing protocols.
Abstract: We present a new dynamic graph structure specifically suited
for largescale transportation networks that provides simultaneously three
unique features: compactness, agility and dynamicity. We demonstrate
its practicality and superiority by conducting an experimental study for
shortest route planning in largescale European and US road networks
with a few dozen millions of nodes and edges. Our approach is the first
one that concerns the dynamic maintenance of a largescale graph with
ordered elements using a contiguous memory part, and which allows an
arbitrary online reordering of its elements.
Abstract: In this work we present the architecture and implementation of WebDust, a software platform for managing multiple, heterogeneous (both in terms of software and hardware), geographically disparate sensor networks. We describe in detail the main concepts behind its design, and basic aspects of its implementation, including the services provided to endusers and developers. WebDust uses a peertopeer substrate, based on JXTA, in order to unify multiple sensor networks installed in various geographic areas. We aim at providing a software framework that will permit developers to deal with the new and critical aspects that networks of sensors and tiny devices bring into global computing, and to provide a coherent set of high level services, design rules and technical recommendations, in order to be able to develop the envisioned applications of global sensor networks. Furthermore, we give an overview of a deployed distributed testbed, consisting of a total 56 nodes and describing in more detail two specific testbed sites and the integration of the related software and hardware technologies used for its operation with our platform. Finally, we describe the design and implementation of an interface option provided to endusers, based on the popular Google Earth application.
Abstract: We study the problem of data propagation in sensor networks,
comprised of a large number of very small and lowcost nodes,
capable of sensing, communicating and computing. The distributed
cooperation of such nodes may lead to the accomplishment of large
sensing tasks, having useful applications in practice. We present
a new protocol for data propagation towards a control center
(``sink") that avoids flooding by probabilistically favoring
certain (``close to optimal") data transmissions.
This protocol is very simple to implement in sensor devices
and operates under total absence
of coordination between sensors. We consider a network model of randomly deployed sensors of sufficient density.
As shown by a geometry analysis,
the protocol is correct, since it always propagates data
to the sink, under ideal network conditions (no failures). Using
stochastic processes, we show that the protocol is very energy efficient. Also, when part of the network is inoperative, the
protocol manages to propagate data very close to the sink, thus in
this sense it is robust. We finally present and discuss
largescale experimental findings validating the analytical
results.
Abstract: We study the problem of data propagation in sensor networks,
comprised of a large number of very small and lowcost nodes,
capable of sensing, communicating and computing. The distributed
cooperation of such nodes may lead to the accomplishment of large
sensing tasks, having useful applications in practice. We present a new protocol for data propagation towards a control center ("sink") that avoids flooding by probabilistically favoring certain ("close to optimal") data transmissions. Motivated by certain applications and also as a starting point for a rigorous analysis, we study here latticeshaped sensor networks. We however show that this lattice shape emerges even in randomly deployed sensor networks of sufficient sensor density. Our work is inspired and builds upon the directed diffusion paradigm.
This protocol is very simple to implement in sensor devices, uses only local information and operates under total absence of coordination between sensors. We consider a network model of randomly deployed sensors of sufficient density. As shown by a geometry analysis, the protocol is correct, since it always propagates data to the sink, under ideal network conditions (no failures). Using stochastic processes, we show that the protocol is very energy efficient. Also, when part of the network is inoperative, the protocol manages to propagate data very close to the sink, thus in this sense it is robust. We finally present and discuss largescale experimental findings validating the analytical results.
Abstract: In this paper, a new service oriented networking
paradigm is presented, where network nodes (peers) are self
organized into individual service entities. The key idea relies on
the overlay approach, where there exists a virtual service plane,
fragmented into selforganized and selfmanaged entities called
islands of service transparency. The islands are formed in an
upstream, adhoc mode from the nonnetworking resources (i.e
VoD, grid server, etc) towards all ingress routers of the network,
using link state advertisements and multicost path selection
algorithms (i.e residual bandwidth, server capacity, storage, etc).
Organization and reorganization of nodes around nonnetwork
resources is transparent to endusers, and thus any request
within a specific service island is transparently routed to the
island’s resource for execution. A service proxy is commissioned
to resolve service addresses and service attributes to QoS metrics.
In this paper, we present the main notations and metrics of the
proposed architecture as well as node behavior and potential
GMPLS extensions for implementation issues
Abstract: We propose a MAC protocol for mobile ad hoc networks that
uses power control for the RTS/CTS and DATA frame
transmissions in order to improve energy and capacity
utilization efficiency. Unlike IEEE 802.11, in our scheme the
RTS frames are not sent using the maximum transmission
power to silence neighbouring nodes, and the CTS frames do
not silence all receiving nodes to the same degree. In contrast,
the transmission power of the RTS frames follows a slow
start principle, while the CTS frames, which are sent at
maximum transmission power, prevent the neighbouring
nodes from transmitting their DATA frames with power more
than a computed threshold, while allowing them to transmit at
power levels less than that threshold. This is done by
including in the RTS and the CTS frames additional
information, such as the power of the transmissions, and the
interference tolerance of the nodes. Moreover the DATA
frames are sent at the minimum required transmission power
increased by a small margin to ensure connectivity with the
intended receiver, so as to cause minimal interference to
neighbouring nodes and allow for future interference to be
added to the receiver of the DATA frames. The power to be
used by the transmitter is computed by the recipient of the
RTS frame and is included in the CTS frame. It is expected
that a network with such a power management scheme would
achieve a better throughput performance and more power
savings than a network without such a scheme.
Abstract: We propose a MAC protocol for mobile ad hoc networks that
uses power control for the RTS/CTS and DATA frame
transmissions in order to improve energy and capacity
utilization efficiency. Unlike IEEE 802.11, in our scheme the
RTS frames are not sent using the maximum transmission
power to silence neighbouring nodes, and the CTS frames do
not silence all receiving nodes to the same degree. In contrast,
the transmission power of the RTS frames follows a slow
start principle, while the CTS frames, which are sent at
maximum transmission power, prevent the neighbouring
nodes from transmitting their DATA frames with power more
than a computed threshold, while allowing them to transmit at
power levels less than that threshold. This is done by
including in the RTS and the CTS frames additional
information, such as the power of the transmissions, and the
interference tolerance of the nodes. Moreover the DATA
frames are sent at the minimum required transmission power
increased by a small margin to ensure connectivity with the
intended receiver, so as to cause minimal interference to
neighbouring nodes and allow for future interference to be
added to the receiver of the DATA frames. The power to be
used by the transmitter is computed by the recipient of the
RTS frame and is included in the CTS frame. It is expected
that a network with such a power management scheme would
achieve a better throughput performance and more power
savings than a network without such a scheme.
Abstract: Motivated by emerging applications, we consider sensor networks where the sensors themselves (not just the sinks) are mobile. Furthermore, we focus on mobility scenarios characterized by heterogeneous, highly changing mobility roles in the network. To capture these high dynamics of diverse sensory motion we propose a novel network parameter,
the mobility level, which, although simple and local, quite accurately takes into account both the spatial and speed characteristics of motion. We then propose adaptive data dissemination protocols that use the mobility level estimation to optimize performance, by basically exploiting high mobility (redundant message ferrying) as a costeffective replacement of flooding, e.g. the sensors tend to dynamically propagate less data in the presence
of high mobility, while nodes of high mobility are favored for moving data around. These dissemination schemes are enhanced by a distancesensitive probabilistic message flooding inhibition mechanism that further reduces communication cost, especially for fast nodes of high mobility level, and as distance to data destination decreases. Our simulation findings
demonstrate significant performance gains of our protocols compared to nonadaptive protocols, i.e. adaptation increases the success rate and reduces latency (even by 15%) while at the same time significantly reducing energy dissipation (in most cases by even 40%). Also, our adaptive schemes achieve significantly higher message delivery ratio and
satisfactory energylatency tradeoffs when compared to flooding when sensor nodes have
limited message queues.
Abstract: We introduce a new modelling assumption for wireless sensor networks, that of node redeployment (addition of sensor devices during protocol evolution) and we extend the modelling assumption of heterogeneity (having sensor devices of various types). These two features further increase the highly dynamic nature of such networks and adaptation becomes a powerful technique for protocol design. Under these modelling assumptions, we design, implement and evaluate a new power conservation scheme for efficient data propagation. Our scheme is adaptive: it locally monitors the network conditions (density, energy) and accordingly adjusts the sleepawake schedules of the nodes towards improved operation choices. The scheme is simple, distributed and does not require exchange of control messages between nodes.
Implementing our protocol in software we combine it with two wellknown data propagation protocols and evaluate the achieved performance through a detailed simulation study using our extended version of the network simulator ns2. We focus on highly dynamic scenarios with respect to network density, traffic conditions and sensor node resources. We propose a new general and parameterized metric capturing the tradeoffs between delivery rate, energy efficiency and latency. The simulation findings demonstrate significant gains (such as more than doubling the success rate of the wellknown Directed Diffusion propagation protocol) and good tradeoffs achieved. Furthermore, the redeployment of additional sensors during network evolution and/or the heterogeneous deployment of sensors, drastically improve (when compared to ``equal total power" simultaneous deployment of identical sensors at the start) the protocol performance (i.e. the success rate increases up to four times} while reducing energy dissipation and, interestingly, keeping latency low).
Abstract: Clustering is a crucial network design approach to enable largescale wireless sensor networks (WSNs) deployments. A large variety of clustering approaches has been presented focusing on different performance metrics. Such protocols usually aim at minimizing communication overhead, evenly distributing roles among the participating nodes, as well as controlling the network topology. Simulations on such protocols are performed using theoretical models that are based on unrealistic assumptions like the unit disk graph communication model, ideal wireless communication channels and perfect energy consumption estimations. With these assumptions taken for granted, theoretical models claim various performance milestones that cannot be achieved in realistic conditions. In this paper, we design a new clustering protocol that adapts to the changes in the environment and the needs and goals of the user applications. We address the issues that hinder its performance due to the real environment conditions and provide a deployable protocol. The implementation, integration and experimentation of this new protocol and it's optimizations, were performed using the \textsf{WISEBED} framework. We apply our protocol in multiple indoors wireless sensor testbeds with multiple experimental scenarios to showcase scalability and tradeoffs between network properties and configurable protocol parameters. By analysis of the real world experimental output, we present results that depict a more realistic view of the clustering problem, regarding adapting to environmental conditions and the quality of topology control. Our study clearly demonstrates the applicability of our approach and the benefits it offers to both research \& development communities.
Abstract: Wireless Sensor Networks are by nature highly dynamic and communication between sensors is completely ad hoc, especially when mobile devices are part of the setup. Numerous protocols and applications proposed for such networks
operate on the assumption that knowledge of the neighborhood is a priori available to all nodes. As a result, WSN deployments need to use or implement from scratch a neighborhood discovery mechanism. In this work we present a new protocol based on adaptive periodic beacon exchanges. We totally avoid continuous beaconing by adjusting the rate of broadcasts using the concept of consistency over the understanding of neighborhood that nearby devices share. We propose, implement and evaluate our adaptive neighborhood discovery protocol over our experimental testbed and using large scale simulations. Our results indicate that the
new protocol operates more eciently than existing reference implementations while it provides valid information to applications that use it. Extensive performance evaluation indicates that it successfully reduces generated network traffic by 90% and increases network lifetime by 20% compared to existing mechanisms that rely on continuous beaconing.
Abstract: Motivated by emerging applications, we consider sensor networks where the sensors themselves
(not just the sinks) are mobile. Furthermore, we focus on mobility
scenarios characterized by heterogeneous, highly changing mobility
roles in the network.
To capture these high dynamics of diverse sensory motion
we propose a novel network parameter, the mobility level, which, although
simple and local, quite accurately takes into account both the
spatial and speed characteristics of motion. We then propose
adaptive data dissemination protocols that use the
mobility level estimation to optimize performance, by basically
exploiting high mobility (redundant message ferrying) as a costeffective
replacement of flooding, e.g., the sensors tend to dynamically propagate
less data in the presence of high mobility, while nodes of high mobility
are favored for moving data around.
These dissemination schemes are enhanced by a distancesensitive
probabilistic message flooding inhibition mechanism that
further reduces communication cost, especially for fast nodes
of high mobility level, and as distance to data destination
decreases. Our simulation findings demonstrate significant
performance gains of our protocols compared to nonadaptive
protocols, i.e., adaptation increases the success rate and reduces
latency (even by 15\%) while at the same time significantly
reducing energy dissipation (in most cases by even 40\%).
Also, our adaptive schemes achieve significantly
higher message delivery ratio and satisfactory energylatency
tradeoffs when compared to flooding when sensor nodes have limited message queues.
Abstract: Motivated by emerging applications, we consider sensor networks where the sensors themselves
(not just the sinks) are mobile. We focus on mobility
scenarios characterized by heterogeneous, highly changing mobility
roles in the network.
To capture these high dynamics
we propose a novel network parameter, the mobility level, which, although
simple and local, quite accurately takes into account both the
spatial and speed characteristics of motion. We then propose
adaptive data dissemination protocols that use the
mobility level estimation to improve performance. By basically
exploiting high mobility (redundant message ferrying) as a costeffective
replacement of flooding, e.g., the sensors tend to dynamically propagate
less data in the presence of high mobility, while nodes of high mobility
are favored for moving data around.
These dissemination schemes are enhanced by a distancesensitive
probabilistic message flooding inhibition mechanism that
further reduces communication cost, especially for fast nodes
of high mobility level, and as distance to data destination
decreases. Our simulation findings demonstrate significant
performance gains of our protocols compared to nonadaptive
protocols, i.e., adaptation increases the success rate and reduces
latency (even by 15\%) while at the same time significantly
reducing energy dissipation (in most cases by even 40\%).
Also, our adaptive schemes achieve significantly
higher message delivery ratio and satisfactory energylatency
tradeoffs when compared to flooding when sensor nodes have limited message queues.
Abstract: We consider sensor networks where the sensor nodes are attached on entities that move in a highly dynamic, heterogeneous manner. To capture this mobility diversity we introduce a new network parameter, the directionaware mobility
level, which measures how fast and close each mobile node is expected to get to the data destination (the sink). We then provide local, distributed data dissemination protocols
that adaptively exploit the node mobility to improve performance. In particular, "high" mobility is used as a low cost replacement for data dissemination (due to the ferrying of data), while in the case of "low" mobility either a) data propagation redundancy is increased (when highly mobile neighbors exist) or b) longdistance data transmissions are used (when the entire neighborhood is of low mobility) to accelerate data dissemination towards the sink. An extensive performance comparison to relevant methods from
the state of the art demonstrates signicant improvements i.e. latency is reduced by even 4 times while keeping energy dissipation and delivery success at very satisfactory levels.
Abstract: We investigate the problem of ecient wireless energy recharging in Wireless Rechargeable Sensor Networks (WRSNs). In
such networks a special mobile entity (called the Mobile Charger) traverses the network and wirelessly replenishes the energy
of sensor nodes. In contrast to most current approaches, we envision methods that are distributed, adaptive and use limited
network information. We propose three new, alternative protocols for ecient recharging, addressing key issues which we
identify, most notably (i) to what extent each sensor should be recharged (ii) what is the best split of the total energy between
the charger and the sensors and (iii) what are good trajectories the MC should follow. One of our protocols (
LRP
) performs
some distributed, limited sampling of the network status, while another one (
RTP
) reactively adapts to energy shortage alerts
judiciously spread in the network. As detailed simulations demonstrate, both protocols signicantly outperform known state
of the art methods, while their performance gets quite close to the performance of the global knowledge method (
GKP
) we
also provide, especially in heterogeneous network deployments.
Abstract: We introduce a new modelling assumption in wireless sensor networks, that of node redeployment (addition of sensor devices during the protocol evolution) and we extend the modelling assumption of heterogeneity (having sensor devices of various types). These two features further increase the highly dynamic nature of such networks and adaptation becomes a powerful technique for protocol design. Under this model, we design, implement and evaluate a power conservation scheme for efficient data propagation. Our protocol is adaptive: it locally monitors the network conditions (density, energy) and accordingly adjusts the sleepawake schedules of the nodes towards best operation choices. Our protocol operates does not require exchange of control messages between nodes to coordinate.Implementing our protocol we combine it with two wellknown data propagation protocols and evaluate the achieved performance through a detailed simulation study using our extended version of Ns2. We focus in highly dynamic scenarios with respect to network density, traffic conditions and sensor node resources. We propose a new general and parameterized metric capturing the tradeoff between delivery rate, energy efficiency and latency. The simulation findings demonstrate significant gains (such as more than doubling the success rate of the wellknown Directed Diffusion propagation paradigm) and good tradeoffs. Furthermore, redeployment of sensors during network evolution and/or heterogeneous deployment of sensors drastically improve (when compared to equal total "power" simultaneous deployment of identical sensors at the start) the protocol performance (the success rate increases up to four times while reducing energy dissipation and, interestingly, keeping latency low).
Abstract: The “small world” phenomenon, i.e., the fact that the
global social network is strongly connected in the sense
that every two persons are interrelated through a small
chain of friends, has attracted research attention and has
been strongly related to the results of the social
psychologist¢s Stanley Milgram experiments; properties
of social networks and relevant problems also emerge in
peertopeer systems and their study can shed light on
important modern network design properties.
In this paper, we have experimentally studied greedy
routing algorithms, i.e., algorithms that route information
using “longrange” connections that function as
shortcuts connecting “distant” network nodes. In
particular, we have implemented greedy routing
algorithms, and techniques from the recent literature in
networks of line and grid topology using parallelization
for increasing efficiency. To the best of our knowledge, no
similar attempt has been made so far
Abstract: A temporal graph is, informally speaking, a graph that changes with time. When time is discrete and only the relationships between the participating entities may change and not the entities themselves, a temporal graph may be viewed as a sequence G1,G2…,Gl of static graphs over the same (static) set of nodes V. Though static graphs have been extensively studied, for their temporal generalization we are still far from having a concrete set of structural and algorithmic principles. Recent research shows that many graph properties and problems become radically different and usually substantially more difficult when an extra time dimension in added to them. Moreover, there is already a rich and rapidly growing set of modern systems and applications that can be naturally modeled and studied via temporal graphs. This, further motivates the need for the development of a temporal extension of graph theory. We survey here recent results on temporal graphs and temporal graph problems that have appeared in the Computer Science community.
Abstract: Consider k particles, 1 red and k–1 white, chasing each other on the nodes of a graph G. If the red one catches one of the white, it ldquoinfectsrdquo it with its color. The newly red particles are now available to infect more white ones. When is it the case that all white will become red? It turns out that this simple question is an instance of information propagation between random walks and has important applications to mobile computing where a set of mobile hosts acts as an intermediary for the spread of information.
In this paper we model this problem by k concurrent random walks, one corresponding to the red particle and k–1 to the white ones. The infection time Tk of infecting all the white particles with red color is then a random variable that depends on k, the initial position of the particles, the number of nodes and edges of the graph, as well as on the structure of the graph.
We easily get that an upper bound on the expected value of Tk is the worst case (over all initial positions) expected meeting time m* of two random walks multiplied by THgr (log k). We demonstrate that this is, indeed, a tight bound; i.e. there is a graph G (a special case of the ldquolollipoprdquo graph), a range of values k
Abstract: The study of the path coloring problem is motivated by the allocation of optical bandwidth to communication requests in alloptical networks that utilize Wavelength Division Multiplexing (WDM). WDM technology establishes communication between pairs of network nodes by establishing transmitterreceiver paths and assigning wavelengths to each path so that no two paths going through the same fiber link use the same wavelength. Optical bandwidth is the number of distinct wavelengths. Since stateoftheart technology allows for a limited number of wavelengths, the engineering problem to be solved is to establish communication minimizing the total number of wavelengths used. This is known as the wavelength routing problem. In the case where the underlying network is a tree, it is equivalent to the path coloring problem.
We survey recent advances on the path coloring problem in both undirected and bidirected trees. We present hardness results and lower bounds for the general problem covering also the special case of sets of symmetric paths (corresponding to the important case of symmetric communication). We give an overview of the main ideas of deterministic greedy algorithms and point out their limitations. For bidirected trees, we present recent results about the use of randomization for path coloring and outline approximation algorithms that find path colorings by exploiting fractional path colorings. Also, we discuss upper and lower bounds on the performance of online algorithms.
Abstract: A new model for intrusion and its propagation through various attack
schemes in networks is considered. The model is characterized by the number of
network nodes n, and two parameters f and g. Parameter f represents the probability
of failure of an attack to a node and is a gross measure of the level of security of
the attacked system and perhaps of the intruder¢s skills; g represents a limit on
the number of attacks that the intrusion software can ever try, due to the danger
of being discovered, when it issues them from a particular (broken) network node.
The success of the attack scheme is characterized by two factors: the number of
nodes captured (the spread factor) and the number of virtual links that a defense
mechanism has to trace from any node where the attack is active to the origin of
the intrusion (the traceability factor). The goal of an intruder is to maximize both
factors. In our model we present four different ways (attack schemes) by which an
intruder can organize his attacks. Using analytic and experimental methods, we first
show that for any 0 < f < 1, there exists a constant g for which any of our attack
schemes can achieve a {\`E}(n) spread and traceability factor with high probability,
given sufficient propagation time. We also show for three of our attack schemes
that the spread and the traceability factors are, with high probability, linearly related
during the whole duration of the attack propagation. This implies that it will not be
easy for a detection mechanism to trace the origin of the intrusion, since it will have
to trace a number of links proportional to the nodes captured.
Abstract: A new model for intrusion and its propagation through various attack
schemes in networks is considered. The model is characterized by the number of
network nodes n, and two parameters f and g. Parameter f represents the probability
of failure of an attack to a node and is a gross measure of the level of security of
the attacked system and perhaps of the intruder¢s skills; g represents a limit on
the number of attacks that the intrusion software can ever try, due to the danger
of being discovered, when it issues them from a particular (broken) network node.
The success of the attack scheme is characterized by two factors: the number of
nodes captured (the spread factor) and the number of virtual links that a defense
mechanism has to trace from any node where the attack is active to the origin of
the intrusion (the traceability factor). The goal of an intruder is to maximize both
factors. In our model we present four different ways (attack schemes) by which an
intruder can organize his attacks. Using analytic and experimental methods, we first
show that for any 0 < f < 1, there exists a constant g for which any of our attack
schemes can achieve a (n) spread and traceability factor with high probability,
given sufficient propagation time. We also show for three of our attack schemes
that the spread and the traceability factors are, with high probability, linearly related
during the whole duration of the attack propagation. This implies that it will not be
easy for a detection mechanism to trace the origin of the intrusion, since it will have
to trace a number of links proportional to the nodes captured.
Abstract: In this paper, we present BAD, an applicationlevel multi
cast infrastructure. BAD is designed to improve the perfor
mance of multicast dissemination trees, under both a static
and a dynamic environment, where the eective bandwidth
of the network links changes with time. Its main goal is
to improve the data rate that end users perceive during
a multicast operation. BAD can be used for the creation
and management of multicast groups. It can be deployed
over any DHT retaining its fundamental advantages of band
width improvement. BAD consists of a suit of algorithms
for node joins/leaves, bandwidth distribution to heteroge
neous nodes, tree rearrangement and reduction of overhead.
We have implemented BAD within the FreePastry system.
We report on the results of a detailed performance evalua
tion which testies for BAD's eciency and low overhead.
Specically, our experiments show that the improvement on
the minimum bandwidth ranges from 40% to 1400% and the
improvement on the average bandwidth ranges from 60% to
250%.
Abstract: We study the fundamental naming and counting problems in networks that are anonymous, unknown, and possibly dynamic. Network dynamicity is modeled by the 1interval connectivity model [KLO10]. We first prove that on static networks with broadcast counting is impossible to solve without a leader and that naming is impossible to solve even with a leader and even if nodes know n. These impossibilities carry over to dynamic networks as well. With a leader we solve counting in linear time. Then we focus on dynamic networks with broadcast. We show that if nodes know an upper bound on the maximum degree that will ever appear then they can obtain an upper bound on n. Finally, we replace broadcast with onetoeach, in which a node may send a different message to each of its neighbors. This variation is then proved to be computationally equivalent to a fullknowledge model with unique names.
Abstract: In this work, we study the propagation of influence and computation in dynamic networks that are possibly disconnected at every instant. We focus on a synchronous message passing communication model with broadcast and bidirectional links. To allow for bounded endtoend communication we propose a set of minimal temporal connectivity conditions that bound from the above the time it takes for information to make progress in the network. We show that even in dynamic networks that are disconnected at every instant information may spread as fast as in networks that are connected at every instant. Further, we investigate termination criteria when the nodes know some upper bound on each of the temporal connectivity conditions. We exploit our termination criteria to provide efficient protocols (optimal in some cases) that solve the fundamental counting and alltoall token dissemination (or gossip) problems. Finally, we show that any protocol that is correct in instantaneous connectivity networks can be adapted to work in temporally connected networks.
Abstract: The Team Orienteering Problem with Time Windows (TOPTW)
deals with deriving a number of tours comprising a subset of candidate
nodes (each associated with a \prot" value and a visiting time window)
so as to maximize the overall \prot", while respecting a specied time
span. TOPTW has been used as a reference model for the Tourist Trip
Design Problem (TTDP) in order to derive nearoptimal multipleday
tours for tourists visiting a destination featuring several points of inter
est (POIs), taking into account a multitude of POI attributes. TOPTW
is an NPhard problem and the most ecient known heuristic is based on
Iterated Local Search (ILS). However, ILS treats each POI separately;
hence it tends to overlook highly protable areas of POIs situated far
from the current location, considering them too timeexpensive to visit.
We propose two clusterbased extensions to ILS addressing the afore
mentioned weakness by grouping POIs on disjoint clusters (based on
geographical criteria), thereby making visits to such POIs more attrac
tive. Our approaches improve on ILS with respect to solutions quality,
while executing at comparable time and reducing the frequency of overly
long transfers among POIs.
Abstract: One problem that frequently arises is the establishment of a
secure connection between two network nodes. There are many key
establishment protocols that are based on Trusted Third Parties or
public key cryptography which are in use today. However, in the
case of networks with frequently changing topology and size
composed of nodes of limited computation power, such as the adhoc
and sensor networks, such an approach is difficult to apply. One
way of attacking this problem for such networks is to have the two
nodes share some piece of information that will, subsequently,
enable them to transform this information into a shared
communication key.
%
Having each pair of network nodes share some piece of information
is, often, achieved through appropriate {\em key predistribution}
schemes. These schemes work by equipping each network node with a
set of candidate key values, some of which shared with other
network nodes possessing other keys sets. Later, when two nodes
meet, they can employ a suitable key establishment protocol in
order to locate shared values and used them for the creation of
the communication key.
%
In this paper we give a formal definition of collusion resistant
key predistribution schemes and then propose such a scheme based
on probabilistically created set systems. The resulting key sets
are shown to have a number of desirable properties that ensure the
confidentiality of communication sessions against collusion
attacks by other network nodes.
Abstract: An intersection graph of n vertices assumes that each vertex is equipped with a subset of a global label set. Two vertices share an edge
when their label sets intersect. Random Intersection Graphs (RIGs) (as defined in [18, 31]) consider label sets formed by the following experiment:
each vertex, independently and uniformly, examines all the labels (m in total) one by one. Each examination is independent and the vertex
succeeds to put the label in her set with probability p. Such graphs nicely capture interactions in networks due to sharing of resources among nodes.
We study here the problem of efficiently coloring (and of finding upper bounds to the chromatic number) of RIGs. We concentrate in a range
of parameters not examined in the literature, namely: (a) m = n{\'a} for less than 1 (in this range, RIGs differ substantially from the Erd¨os Renyi random graphs) and (b) the selection probability p is quite high
(e.g. at least ln2 n m in our algorithm) and disallows direct greedy colouring methods.
We manage to get the following results:
For the case mp ln n, for any constant < 1 − , we prove that np colours are enough to colour most of the vertices of the graph with high probability (whp). This means that even for quite dense
graphs, using the same number of colours as those needed to properly colour the clique induced by any label suffices to colour almost all of the vertices of the graph. Note also that this range of values of m, p
is quite wider than the one studied in [4].
� We propose and analyze an algorithm CliqueColour for finding a proper colouring of a random instance of Gn,m,p, for any mp >=ln2 n. The algorithm uses information of the label sets assigned to the
vertices of Gn,m,p and runs in O (n2mp2/ln n) time, which is polynomial in n and m. We also show by a reduction to the uniform random
intersection graphs model that the number of colours required by the algorithm are of the correct order of magnitude with the actual
chromatic number of Gn,m,p.
⋆ This work was partially supported by the ICT Programme of the European Union under contract number ICT2008215270 (FRONTS). Also supported by Research Training Group GK693 of the Paderborn Institute for Scientific Computation
(PaSCo).
� We finally compare the problem of finding a proper colouring for Gn,m,p to that of colouring hypergraphs so that no edge is monochromatic.We show how one can find in polynomial time a kcolouring of the vertices of Gn,m,p, for any integer k, such that no clique induced by only one label in Gn,m,p is monochromatic. Our techniques are novel and try to exploit as much as possible the hidden structure of random intersection graphs in this interesting range.
Abstract: We investigate random intersection graphs, a combinatorial model that quite accurately abstracts distributed networks with local interactions between nodes blindly sharing critical resources from a limited globally available domain. We study important combinatorial properties (independence and hamiltonicity) of such graphs. These properties relate crucially to algorithmic design for important problems (like secure communication and frequency assignment) in distributed networks characterized by dense, local interactions and resource limitations, such as sensor networks. In particular, we prove that, interestingly, a small constant number of random, resource selections suffices to make the graph hamiltonian and we provide tight evaluations of the independence number of these graphs.
Abstract: The problem of communication among mobile nodes is one of the most fundamental problems in ad hoc mobile networks and is at the core of many algorithms, such as for counting the number of nodes, electing a leader, data processing etc. For an exposition of several important problems in ad hoc mobile networks. The work of Chatzigiannakis, Nikoletseas and Spirakis focuses on wireless mobile networks that are subject to highly dynamic structural changes created by mobility, channel fluctuations and device failures. These changes affect topological connectivity, occur with high frequency and may not be predictable in advance. Therefore, the environment where the nodes move (in threedimensional space with possible obstacles) as well as the motion that the nodes perform are \textit{input} to any distributed algorithm.
Abstract: We study the problem of maintaining connectivity in a wireless
network where the network nodes are equipped with
directional antennas. Nodes correspond to points on the
plane and each uses a directional antenna modeled by a sector
with a given angle and radius. The connectivity problem
is to decide whether or not it is possible to orient the antennas
so that the directed graph induced by the node transmissions
is strongly connected. We present algorithms for
simple polynomialtimesolvable cases of the problem, show
that the problem is NPcomplete in the 2dimensional case
when the sector angle is small, and present algorithms that
approximate the minimum radius to achieve connectivity for
sectors with a given angle. We also discuss several extensions
to related problems. To the best of our knowledge, the
problem has not been studied before in the literature.
Abstract: This paper addresses the problem of counting the size of a network where (i) processes have the same identifiers (anonymous nodes) and (ii) the et
work topology constantly changes (dynamic network). Changes are riven by a powerful adversary that can look at internal process states and add and remove edges in order to contrast the convergence of the algorithm to the correct count. The paper proposes two leaderbased counting algorithms. Such algorithms are based on a technique that mimics an energytransfer between network nodes. The first algorithm assumes that the adversary cannot generate either disconnected network graphs or network graphs where nodes have degree greater than D. In such algorithm, the leader can count the size of the network and detect the counting termination in a finite time (i.e., conscious counting algorithm). The second algorithm assumes that the adversary only keeps the network graph connected at any time and we prove that the leader can still converge to a correct count in a finite number of rounds, but it is not conscious when this convergence happens.
Abstract: Everincreasing bandwidth demands and higher flexibility are the main challenges for the next generation optical core networks. A new trend in order to address these challenges is to consider the impairments of the lightpaths during the design of optical networks. In our work, we focus on translucent optical networks, where some lightpaths are routed transparently, whereas others go through a number of regenerators. We present a cost analysis of design strategies, which are based either on an exact Quality of Transmission (QoT) validation or on a relaxed one and attempt to reduce the amount of regenerators used. In the exact design strategy, regenerators are required if the QoT of a candidate lightpath is below a predefined threshold, assuming empty network conditions. In the relaxed strategy, this predefined threshold is lower, while it is assumed that the network is fully loaded. We evaluate technoeconomically the suggested design solutions and also show that adding more flexibility to the optical nodes has a large impact to the total infrastructure cost.
Abstract: Counting in general, and estimating the cardinality of (multi) sets in particular, is highly desirable for a large variety of applications, representing a foundational block for the efficient deployment and access of emerging internetscale information systems. Examples of such applications range from optimizing query access plans in internetscale databases, to evaluating the significance (rank/score) of various data items in information retrieval applications. The key constraints that any acceptable solution must satisfy are: (i) efficiency: the number of nodes that need be contacted for counting purposes must be small in order to enjoy small latency and bandwidth requirements; (ii) scalability, seemingly contradicting the efficiency goal: arbitrarily large numbers of nodes nay need to add elements to a (multi) set, which dictates the need for a highly distributed solution, avoiding serverbased scalability, bottleneck, and availability problems; (iii) access and storage load balancing: counting and related overhead chores should be distributed fairly to the nodes of the network; (iv) accuracy: tunable, robust (in the presence of dynamics and failures) and highly accurate cardinality estimation; (v) simplicity and ease of integration: special, solutionspecific indexing structures should be avoided. In this paper, first we contribute a highlydistributed, scalable, efficient, and accurate (multi) set cardinality estimator. Subsequently, we show how to use our solution to build and maintain histograms, which have been a basic building block for query optimization for centralized databases, facilitating their porting into the realm of internetscale data networks.
Abstract: Random walks in wireless sensor networks can serve as fully
local, very simple strategies for sink motion that reduce energy dissipa
tion a lot but increase the latency of data collection. To achieve satis
factory energylatency tradeoffs the sink walks can be made adaptive,
depending on network parameters such as density and/or history of past
visits in each network region; but this increases the memory require
ments. Towards better balances of memory/performance, we propose two
new random walks: the Random Walk with Inertia and the Exploreand
Go Random Walk; we also introduce a new metric (Proximity Varia
tion) that captures the different way each walk gets close to the network
nodes. We implement the new walks and experimentally compare them
to known ones. The simulation findings demonstrate that the new walk¢s
performance (cover time) gets close to the one of the (much stronger)
biased walk, while in some other respects (partial cover time, proximity
variation) they even outperform it. We note that the proposed walks
have been finetuned in the light of experimental findings.
Abstract: We present a new overlay, called the Deterministic Decentral
ized tree (D2tree). The D2tree compares favourably to other overlays for
the following reasons: (a) it provides matching and better complexities,
which are deterministic for the supported operations; (b) the manage
ment of nodes (peers) and elements are completely decoupled from each
other; and (c) an e±cient deterministic loadbalancing mechanism is pre
sented for the uniform distribution of elements into nodes, while at the
same time probabilistic optimal bounds are provided for the congestion
of operations at the nodes.
Abstract: Evaluating target tracking protocols for wireless sensor networks that can localize multiple mobile devices, can be a very challenging task. Such protocols usually aim at minimizing communication overhead, data processing for the participating nodes, as well as delivering adequate tracking information of the mobile targets in a timely manner. Simulations on such protocols are performed using theoretical models that are based on unrealistic assumptions like the unit disk graph communication model, ideal network localization and perfect distance estimations. With these assumptions taken for granted, theoretical models claim various performance milestones that cannot be achieved in realistic conditions. In this paper we design a new localization protocol, where mobile assets can be tracked passively via software agents. We address the issues that hinder its performance due to the real environment conditions and provide a deployable protocol. The implementation, integration and experimentation of this new protocol and it's optimizations, were performed using the WISEBED framework. We apply our protocol in multiple indoors wireless sensor testbeds with multiple experimental scenarios to showcase scalability and tradeoffs between network properties and configurable protocol parameters. By analysis of the real world experimental output, we present results that depict a more realistic view of the target tracking problem, regarding power consumption and the quality of tracking information. Finally we also conduct some very focused simulations to assess the scalability of our protocol in very large networks and multiple mobile assets.
Abstract: Wireless Sensor Networks consist of a large number of small, autonomous devices, that are able to interact with their inveronment by sensing and collaborate to fulfill their tasks, as, usually, a single node is incapable of doing so; and they use wireless communication to enable this collaboration. Each device has limited computational and energy resources, thus a basic issue in the applicastions of wireless sensor networks is the low energy consumption and hence, the maximization of the network lifetime.
The collected data is disseminated to a static control point – data sink in the network, using node to node  multihop data propagation. However, sensor devices consume significant amounts of energy in addition to increased implementation complexity, since a routing protocol is executed. Also, a point of failure emerges in the area near the control center where nodes relay the data from nodes that are farther away. Recently, a new approach has been developed that shifts the burden from the sensor nodes to the sink. The main idea is that the sink has significant and easily replenishable energy reserves and can move inside the area the sensor network is deployed, in order to acquire the data collected by the sensor nodes at very low energy cost. However, the need to visit all the regions of the network may result in large delivery delays.
In this work we have developed protocols that control the movement of the sink in wireless sensor networks with nonuniform deployment of the sensor nodes, in order to succeed an efficient (with respect to both energy and latency) data collection. More specifically, a graph formation phase is executed by the sink during the initialization: the network area is partitioned in equal square regions, where the sink, pauses for a certain amount of time, during the network traversal, in order to collect data.
We propose two network traversal methods, a deterministic and a random one. When the sink moves in a random manner, the selection of the next area to visit is done in a biased random manner depending on the frequency of visits of its neighbor areas. Thus, less frequently visited areas are favored. Moreover, our method locally determines the stop time needed to serve each region with respect to some global network resources, such as the initial energy reserves of the nodes and the density of the region, stopping for a greater time interval at regions with higher density, and hence more traffic load. In this way, we achieve accelerated coverage of the network as well as fairness in the service time of each region.Besides randomized mobility, we also propose an optimized deterministic trajectory without visit overlaps, including direct (onehop) sensortosink data transmissions only.
We evaluate our methods via simulation, in diverse network settings and comparatively to related state of the art solutions. Our findings demonstrate significant latency and energy consumption improvements, compared to previous research.
Abstract: Wireless sensor networks are a recently introduced category of ad hoc computer networks, which are comprised by nodes of small size and limited computing and energy resources. Such nodes are able of measuring physical properties such as temperature, humidity, etc., wireless communication between each other and in some cases interaction with their surrounding environments (through the use of electromechanical parts).
As these networks have begun to be widely available (in terms of cost and commercial hardware availability), their field of application and philosophy of use is constantly evolving. We have numerous examples of their applications, ranging from monitoring the biodiversity of a specific outdoor area to structural health monitoring of bridges, and also networks ranging from few tens of nodes to even thousands of nodes.
In this PhD thesis we investigated the following basic research lines related to wireless sensor networks:
a) their simulation,
b) the development of data propagation protocols suited to such networks and their evaluation through simulation,
c) the modelling of ``hostile'' circumstances (obstacles) during their operation and evaluation of their impact through simulation,
d) the development of a sensor network management application.
Regarding simulation, we initially placed an emphasis to issues such as the effective simulation of networks of several thousands of nodes, and in that respect we developed a network simulator (simDust), which is extendable through the addition of new data propagation protocols and visualization capabilities. This simulator was used to evaluate the performance of a number of characteristic data propagation protocols for wireless sensor networks. Furthermore, we developed a new protocol (VRTP) and evaluated its performance against other similar protocols. Our studies show that the new protocol, that uses dynamic changes of the transmission range of the network nodes, performs better in certain cases than other related protocols, especially in networks containing obstacles and in the case of nonhomogeneous placement of nodes.
Moreover, we emphasized on the addition of ``realistic'' conditions to the simulation of such protocols, that have an adversarial effect on their operation. Our goal was to introduce a model for obstacles that adds little computational overhead to a simulator, and also study the effect of the inclusion of such a model on data propagation protocols that use geographic information (absolute or relative). Such protocols are relatively sensitive to dynamic topology changes and network conditions. Through our experiments, we show that the inclusion of obstacles during simulation can have a significant effect on these protocols.
Finally, regarding applications, we initially proposed an architecture (WebDust/ShareSense), for the management of such networks, that would provide basic capabilities of managing such networks and developing applications above it. Features that set it apart are the capability of managing multiple heterogeneous sensor networks, openess, the use of a peertopeer architecture for the interconnection of multiple sensor network. A large part of the proposed architecture was implemented, while the overall architecture was extended to also include additional visualization capabilities.
Abstract: Wireless sensor networks are comprised of a vast number of devices, situated in an area of interest that self organize in a structureless network, in order to monitor/record/measure an environmental variable or phenomenon and subsequently to disseminate the data to the control center.
Here we present research focused on the development, simulation and evaluation of energy efficient algorithms, our basic goal is to minimize the energy consumption. Despite technology advances, the problem of energy use optimization remains valid since current and emerging hardware solutions fail to solve it.
We aim to reduce communication cost, by introducing novel techniques that facilitate the development of new algorithms. We investigated techniques of distributed adaptation of the operations of a protocol by using information available locally on every node, thus through local choices we improve overall performance. We propose techniques for collecting and exploiting limited local knowledge of the network conditions. In an energy efficient manner, we collect additional information which is used to achieve improvements such as forming energy efficient, low latency and fault tolerant paths to route data. We investigate techniques for managing mobility in networks where movement is a characteristic of the control center as well as the sensors. We examine methods for traversing and covering the network field based on probabilistic movement that uses local criteria to favor certain areas.
The algorithms we develop based on these techniques operate a) at low level managing devices, b) on the routing layer and c) network wide, achieving macroscopic behavior through local interactions. The algorithms are applied in network cases that differ in density, node distribution, available energy and also in fundamentally different models, such as under faults, with incremental node deployment and mobile nodes. In all these settings our techniques achieve significant gains, thus distinguishing their value as tools of algorithmic design.
Abstract: A central problem in distributed computing and telecommunications
is the establishment of common knowledge between two computing
entities. An immediate use of such common knowledge is in the
initiation of a secure communication session between two entities
since the two entities may use this common knowledge in order to
produce a secret key for use with some symmetric cipher.
%
The dynamic establishment of shared information (e.g. secret key)
between two entities is particularly important in networks with no
predetermined structure such as wireless mobile adhoc networks.
In such networks, nodes establish and terminate communication
sessions dynamically with other nodes which may have never been
encountered before in order to somehow exchange information which
will enable them to subsequently communicate in a secure manner.
%
In this paper we give and theoretically analyze a protocol that
enables two entities initially possessing a string each to
securely eliminate inconsistent bit positions, obtaining strings
with a larger percentage of similarities. This can help the nodes
establish a shared set of bits and use it as a key with some
shared key encryption scheme.
Abstract: We here present Fun in Numbers (FinN), a framework for developing pervasive applications and interactive installations for entertainment and educational purposes. Using ad hoc mobile wireless sensor network nodes as the enabling devices, FinN allows for the quick prototyping of applications that utilize input from multiple physical sources (sensors and other means of interfacing), by offering a set of programming templates and services, such as topology discovery, localization and synchronization, that hide the underlying complexity. We present the target application domains of FinN, along with a set of multiplayer games and interactive installations. We describe the overall architecture of our platform
and discuss some key implementation issues of the application domains. Finally, we present the experience gained by deploying the applications developed with our platform.
Abstract: Counting items in a distributed system, and estimating the cardinality of multisets in particular,
is important for a large variety of applications and a fundamental building block for emerging Internetscale information systems. Examples of such applications range from optimizing query access plans in peertopeer data sharing, to computing the significance (rank/score) of data items in distributed information retrieval. The general formal problem addressed in this article is computing the networkwide distinct number of items with some property (e.g., distinct files with file name
containing “spiderman”) where each node in the network holds an arbitrary subset, possibly overlapping the subsets of other nodes. The key requirements that a viable approach must satisfy are:
(1) scalability towards very large network size, (2) efficiency regarding messaging overhead, (3) load
balance of storage and access, (4) accuracy of the cardinality estimation, and (5) simplicity and easy
integration in applications. This article contributes the DHS (Distributed Hash Sketches) method
for this problem setting: a distributed, scalable, efficient, and accurate multiset cardinality estimator.
DHSis based on hash sketches for probabilistic counting, but distributes the bits of each counter
across network nodes in a judicious manner based on principles of Distributed Hash Tables, paying
careful attention to fast access and aggregation as well as update costs. The article discusses various
design choices, exhibiting tunable tradeoffs between estimation accuracy, hopcount efficiency, and
load distribution fairness. We further contribute a fullfledged, publicly available, opensource implementation of all our methods, and a comprehensive experimental evaluation for various settings.
Abstract: In this paper we describe a new simulation platform for heterogeneous distributed systems comprised of small programmable objects (e.g., wireless sensor networks) and traditional networked processors. Simulating such systems is complicated because of the need to coordinate compilers and simulators, often with very different interfaces, options, and fidelities.
Our platform (which we call ADAPT) is a flexible and extensible environment that provides a highly scalable simulator with unique characteristics. While the platform provides advanced functionality such as realtime simulation monitoring, custom topologies and scenarios, mixing real and simulated nodes, etc., the effort required by the user and the impact to her code is minimal. We here present its architecture, the most important design decisions, and discuss its distinct features and functionalities. We integrate our simulator to the Sun SPOT platform to enable simulation of sensing applications that employ both lowend and highend devices programmed with different languages that are internetworked with heterogeneous technologies. We believe that ADAPT will make the development of applications that use small programmable objects more widely accessible and will enable researchers to conduct a joint research approach that combines both theory and practice.
Abstract: Topk query processing is a fundamental building block for efficient ranking in a large number of applications. Efficiency is a central issue, especially for distributed settings, when the data is spread across different nodes in a network. This paper introduces novel optimization methods for topk aggregation queries in such distributed environments. The optimizations can be applied to all algorithms that fall into the frameworks of the prior TPUT and KLEE methods. The optimizations address three degrees of freedom: 1) hierarchically grouping input lists into topk operator trees and optimizing the tree structure, 2) computing dataadaptive scan depths for different input sources, and 3) dataadaptive sampling of a small subset of input sources in scenarios with hundreds or thousands of queryrelevant network nodes. All optimizations are based on a statistical cost model that utilizes local synopses, e.g., in the form of histograms, efficiently computed convolutions, and estimators based on order statistics. The paper presents comprehensive experiments, with three different reallife datasets and using the ns2 network simulator for a packetlevel simulation of a large Internetstyle network.
Abstract: We address the issue of measuring distribution fairness in Internetscale networks. This problem has several interesting instances encountered in different applications, ranging from assessing the distribution of load between network nodes for load balancing purposes, to measuring node utilization for optimal resource exploitation, and to guiding autonomous decisions of nodes in networks built with marketbased economic principles. Although some metrics have been proposed, particularly for assessing load balancing algorithms, they fall short. We first study the appropriateness of various known and previously proposed statistical metrics for measuring distribution fairness. We put forward a number of required characteristics for appropriate metrics. We propose and comparatively study the appropriateness of the Gini coefficient (G) for this task. Our study reveals as most appropriate the metrics of G, the fairness index (FI), and the coefficient of variation (CV) in this order. Second, we develop six distributed sampling algorithms to estimate metrics online efficiently, accurately, and scalably. One of these algorithms (2PRWS) is based on two effective optimizations of a basic algorithm, and the other two (the sequential sampling algorithm, LBSHL, and the clustered sampling one, EBSS) are novel, developed especially to estimate G. Third, we show how these metrics, and especially G, can be readily utilized online by higherlevel algorithms, which can now know when to best intervene to correct unfair distributions (in particular, load imbalances). We conclude with a comprehensive experimentation which comparatively evaluates both the various proposed estimation algorithms and the three most appropriate metrics (G, CV, andFI). Specifically, the evaluation quantifies the efficiency (in terms of number of the messages and a latency indicator), precision, and accuracy achieved by the proposed algorithms when estimating the competing fairness metrics. The central conclusion is that the proposed metric, G, can be estimated with a small number of messages and latency, regardless of the skew of the underlying distribution.
Abstract: Using a set of geometric containers to speed up shortest path queries in a weighted graph has been proven a useful tool for dealing with large sparse graphs. Given a layout of a graph G=(V,E), we store, for each edge (u,v)set membership, variantE, the bounding box of all nodes tset membership, variantV for which a shortest utpath starts with (u,v). Shortest path queries can then be answered by DijkstraImage restricted to edges where the corresponding bounding box contains the target.
In this paper, we present new algorithms as well as an empirical study for the dynamic case of this problem, where edge weights are subject to change and the bounding boxes have to be updated. We evaluate the quality and the time for different update strategies that guarantee correct shortest paths in an interesting application to railway information systems, using realworld data from six European countries.
Abstract: We present a new overlay, called the
Deterministic Decentralized tree
(
D
2

tree). The
D
2
tree compares favorably to other overlays for the following reasons: (a)
it provides matching and better complexities,which are deterministic for the supported
operations; (b) the management of nodes (peers) and elements are completely decoupled from each other; and (c) an efficient deterministic loadbalancing mechanism
is presented for the uniform distribution of elements into nodes, while at the same
time probabilistic optimal bounds are provided for the congestion of operations at the
nodes. The loadbalancing scheme of elements into nodes is deterministic and general
enough to be applied to other hierarchical treebased overlays. This loadbalancing
mechanism is based on an innovative lazy weightbalancing mechanism, which is
interesting in its own right.
Abstract: We present a new overlay, called the Deterministic Decentralized tree ( TeXtree). The TeXtree compares favorably to other overlays for the following reasons: (a) it provides matching and better complexities, which are deterministic for the supported operations; (b) the management of nodes (peers) and elements are completely decoupled from each other; and (c) an efficient deterministic loadbalancing mechanism is presented for the uniform distribution of elements into nodes, while at the same time probabilistic optimal bounds are provided for the congestion of operations at the nodes. The loadbalancing scheme of elements into nodes is deterministic and general enough to be applied to other hierarchical treebased overlays. This loadbalancing mechanism is based on an innovative lazy weightbalancing mechanism, which is interesting in its own right.
Abstract: We investigate the problem of ecient wireless energy recharging in Wireless Rechargeable Sensor Networks (WRSNs). In
such networks special mobile entities (called the Mobile Chargers) traverse the network and wirelessly replenish the energy
of sensor nodes. In contrast to most current approaches, we envision methods that are distributed and use limited network
information. We propose four new protocols for ecient recharging, addressing key issues which we identify, most notably (i)
what are good coordination procedures for the Mobile Chargers and (ii) what are good trajectories for the Mobile Chargers.
Two of our protocols (
DC,DCLK
) perform distributed, limited network knowledge coordination and charging, while two others
(
CC,CCGK
) perform centralized, global network knowledge coordination and charging. As detailed simulations demonstrate,
one of our distributed protocols outperforms a known state of the art method, while its performance gets quite close to the
performance of the powerful centralized global knowledge method.
Abstract: The energy balance property (i.e., all nodes having the same energy throughout the network evolution) contributes significantly (along with energy efficiency) to the maximization of the network lifespan and network connectivity. The problem of achieving energy balanced propagation is well studied in static networks, as it has attracted a lot of research attention.
Recent technological advances have enabled sensor devices to be attached to mobile entities of our every day life (e.g. smartphones, cars, PDAs etc), thus introducing the formation of highly mobile sensor networks.
Inspired by the aforementioned applications, this work is (to the best of our knowledge) the first studying the energy balance property in wireless networks where the nodes are highly and dynamically mobile. In particular, in this paper we propose a new diverse mobility model which is easily parameterized and we also present a new protocol which tries to adaptively exploit the inherent node mobility in order to achieve energy balance in the network in an efficient way.
Abstract: In this work we study energy efficient routing strategies
for wireless adhoc networks. In this kind of networks,
energy is a scarce resource and its conservation
and efficient use is a major issue. Our strategy follows
the multicost routing approach, according to which a
cost vector of various parameters is assigned to each
link. The parameters of interest are the number of hops
on a path, and the residual energy and the transmission
power of the nodes on the path. These parameters
are combined in various optimization functions,
corresponding to different routing algorithms, for selecting
the optimal path. We evaluate the routing algorithms
proposed in a number of scenarios, with respect
to energy consumption, throughput and other performance
parameters of interest. From the experiments
conducted we conclude that routing algorithms that take
into account energy related parameters, increase the
lifetime of the network, while achieving better performance
than other approaches, such as minimum hop
routing.
Abstract: In this work, we propose an energyefficient multicasting algorithm
for wireless networks for the case where the transmission
powers of the nodes are fixed. Our algorithm is
based on the multicost approach and selects an optimal
energyefficient set of nodes for multicasting, taking into account:
i) the node residual energies, ii) the transmission
powers used by the nodes, and iii) the set of nodes covered.
Our algorithm is optimal, in the sense that it can
optimize any desired function of the total power consumed
by the multicasting task and the minimum of the current
residual energies of the nodes, provided that the optimization
function is monotonic in each of these parameters. Our
optimal algorithm has nonpolynomial complexity, thus, we
propose a relaxation producing a nearoptimal solution in
polynomial time. The performance results obtained show
that the proposed algorithms outperform established solutions
for energyaware multicasting, with respect to both
energy consumption and network lifetime. Moreover, it is
shown that the nearoptimal multicost algorithm obtains
most of the performance benefits of the optimal multicost
algorithm at a smaller computational overhead.
Abstract: We consider classical lineartime planar separator algorithms, determining for a given planar graph a small subset of the nodes whose removal separates the graph into two components of similar size. These algorithms are based upon Planar Separator Theorems, which guarantee separators of size MediaObjects/InlineFigure1.png and remaining components of size less than 2n/3. In this work, we present a comprehensive experimental study of the algorithms applied to a large variety of graphs, where the main goal is to find separators that do not only satisfy upper bounds but also possess other desirable qualities with respect to separator size and component balance. We propose the usage of fundamental cycles, whose size is at most twice the diameter of the graph, as planar separators: For graphs of small diameter the guaranteed bound is better than the MediaObjects/InlineFigure2.png bounds, and it turns out that this simple strategy almost always outperforms the other algorithms, even for graphs with large diameter.
Abstract: ManyWSN algorithms and applications are based on knowledge
regarding the position of nodes inside the network area.
However, the solution of using GPS based modules in order
to perform localization in WSNs is a rather expensive solution
and in the case of indoor applications, such as smart
buildings, is also not applicable. Therefore, several techniques
have been studied in order to perform relative localization
in WSNs; that is, to compute the position of
a node inside the network area relatively to the position
of other nodes. Many such techniques are based on indicators
like the Radio Signal Strength Indicator (RSSI)
and the Link Quality Indicator (LQI). These techniques are
based on the assumption that there is strong correlation between
the Euclidian distance of the communicating motes
and these indicators. Therefore, high values of RSSI and
LQI should indicate physical proximity of two communicating
nodes. However, these indicators do not depend solely on
distance. Physical obstacles, ambient electromagnetic noise
and interferences from other wireless transmissions also affect
the quality of wireless communication in a stochastic
way. In this paper we propose, implement, experimentally
fine tune and evaluate a localization algorithm that exploits
the stochastic nature of interferences during wireless communications
in order to perform localization in WSNs. Our
algorithm is particularly designed for indoor localisation of
moving people in smart buildings. The localisation achieved
is finegrained, i.e. the position of the target mote is successfully
computed with approximately one meter accuracy.
This finegrained localisation can be used by smart Building
Management Systems in many applications such as room
adaptation to presence. In our scenario, our proposed algorithm is used by a smart room in order to localise the
position of people inside the room and adapt room illumination
accordingly.
Abstract: The technological as well as software advances in
microelectronics and embedded component design have led to the
development of low cost, smallsized devices capable of forming
wireless, adhoc networks and sensing a number of qualities of
their environment, while performing computations that depend
on the sensed qualities as well as information received by their
peers. These sensor networks rely on the collective power of
the separate devices as well as their computational and sensing
capabilities to understand "global" environmental states through
locally sampled information and local sensor interactions. Due
to the locality of the sensor networks, that naturally arises due
to the locality of their communications capabilities, a number
of interesting connections exist between these networks and
geometrical concepts and problems. In this paper we study two
simple problems that pertain to the formation of low power
and low interference communication patterns in fixed topology
sensor networks. We study the problem of using multihop
communication links instead of direct ones as well as the problem
of forming a communication ring of sensor networks so as to
reduce power consumption as well as interference from other
nodes. Our focus is on the connection between sensor networks
and geometrical concepts, rather than on practicality, so as to
highlight their interrelationship.
Abstract: In this work we study the implementation of multicost rout
ing in a distributed way in wireless mobile ad hoc networks.
In contrast to traditional singlecost routing, where each
path is characterized by a scalar, in multicost routing a
vector of cost parameters is assigned to each network link,
from which the cost vectors of candidate paths are calcu
lated. These parameters are combined in various optimiza
tion functions, corresponding to diﬀerent routing algorithms,
for selecting the optimal path. Up until now the performance
of multicost and multiconstrained routing in wireless ad hoc
networks has been evaluated either at a theoretical level or
by assuming that nodes are static and have full knowledge
of the network topology and nodes� state. In the present
paper we assess the performance of multicost routing based
on energyrelated parameters in mobile ad hoc networks by
embedding its logic in the Dynamic Source Routing (DSR)
algorithm, which is a wellknown fully distributed routing
algorithm. We use simulations to compare the performance
of the multicostDSR algorithm to that of the original DSR
algorithm and examine their behavior under various node
mobility scenarios. The results conﬁrm that the multicost
DSR algorithm improves the performance of the network in
comparison to the original DSR algorithm in terms of energy eﬃciency. The multicostDSR algorithm enhances the
performance of the network not only by reducing energy
consumption overall in the network, but also by spreading
energy consumption more uniformly across the network, pro
longing the network lifetime and reducing the packet drop
probability. Furthermore the delay suﬀered by the packets
reaching their destination for the case of the multicostDSR
algorithm is shown to be lower than in the case of the orig
inal DSR algorithm.
Abstract: We propose efficient schemes for informationtheoretically secure
key exchange in the Bounded Storage Model (BSM), where the adversary
is assumed to have limited storage. Our schemes generate a
secret One Time Pad (OTP) shared by the sender and the receiver,
from a large number of public random bits produced by the sender
or by an external source. Our schemes initially generate a small
number of shared secret bits, using known techniques. We introduce
a new method to expand a small number of shared bits to a
much longer, shared key.
Our schemes are tailored to the requirements of sensor nodes
and wireless networks. They are simple, efficient to implement and
take advantage of the fact that practical wireless protocols transmit
data in frames, unlike previous protocols, which assume access to
specific bits in a stream of data. Indeed, our main contribution is
twofold.
On the one hand, we construct schemes that are attractive in
terms of simplicity, computational complexity, number of bits read
from the shared random source and expansion factor of the initial
key to the final shared key.
On the other hand, we show how to transformany existing scheme
for key exchange in BSM into a more efficient scheme in the number
of bits it reads from the shared source, given that the source is
transmitted in frames.
Abstract: In this work, we study the impact of the dynamic changing of the network link capacities on the stability properties of packetswitched networks. Especially, we consider the Adversarial, QuasiStatic Queuing Theory model, where each link capacity may take on only two possible (integer) values, namely 1 and C>1 under a (w,\~{n})adversary. We obtain the following results:
• Allowing such dynamic changes to the link capacities of a network with just ten nodes that uses the LIS (LongestinSystem) protocol for contention–resolution results in instability at rates View the MathML source and for large enough values of C.
• The combination of dynamically changing link capacities with compositions of contention–resolution protocols on network queues suffices for similar instability bounds: The composition of LIS with any of SIS (ShortestinSystem), NTS (NearesttoSource), and FTG (FurthesttoGo) protocols is unstable at rates View the MathML source for large enough values of C.
• The instability bound of the network subgraphs that are forbidden for stability is affected by the dynamic changes to the link capacities: we present improved instability bounds for all the directed subgraphs that were known to be forbidden for stability on networks running a certain greedy protocol.
Abstract: In this work we study the combination of multicost
routing and adjustable transmission power in wireless
ad hoc networks, so as to obtain dynamic energy and
interferenceefficient routes to optimize network performance.
In multicost routing, a vector of cost parameters is
assigned to each network link, from which the cost vectors
of candidate paths are calculated. Only at the end these
parameters are combined in various optimization functions,
corresponding to different routing algorithms, for selecting
the optimal path. The multicost routing problem is a
generalization of the multiconstrained problem, where no
constraints exist, and is also significantly more powerful
than singlecost routing. Since energy is an important
limitation of wireless communications, the cost parameters
considered are the number of hops, the interference caused,
the residual energy and the transmission power of the
nodes on the path; other parameters could also be included,
as desired. We assume that nodes can use power control to
adjust their transmission power to the desired level. The
experiments conducted show that the combination of multicost
routing and adjustable transmission power can lead to
reduced interference and energy consumption, improving
network performance and lifetime.
Abstract: In translucent (or managed reach) WDM optical
networks, regenerators are employed at specific nodes. Some of
the connections in such networks are routed transparently, while
others have to go through a sequence of 3R regenerators that serve
as “refueling stations” to restore their quality of transmission
(QoT). We extend an online multicost algorithm for transparent
networks presented in our previous study [1], to obtain an IARWA
algorithm that works in translucent networks and makes use,
when required, of the regenerators present at certain locations
of the network. To characterize a path, the algorithm uses a
multicost formulation with several cost parameters, including the
set of available wavelengths, the length of the path, the number of
regenerators used, and noise variance parameters that account for
the physical layer impairments. Given a new connection request
and the current utilization state of the network, the algorithm calculates
a set of non dominated candidate paths, meaning that any
path in this set is not inferior with respect to all cost parameters
than any other path. This set consists of all the costeffective (in
terms of the domination relation) and feasible (in terms of QoT)
lightpaths for the given sourcedestination pair, including all the
possible combinations for the utilization of available regenerators
of the network. An optimization function or policy is then applied
to this set in order to select the optimal lightpath. Different optimization
policies correspond to different IARWA algorithms.
We propose and evaluate several optimization policies, such as the
most used wavelength, the best quality of transmission, the least
regeneration usage, or a combination of these rules. Our results
indicate that in a translucent network the employed IARWA
algorithm has to consider all problem parameters, namely, the
QoT of the lightpaths, the utilization of wavelengths and the
availability of regenerators, to efficiently serve the online traffic.
Abstract: In this book chapter we will consider key establishment protocols for wireless sensor networks.
Several protocols have been proposed in the literature for the establishment of a shared group key for wired networks.
The choice of a protocol depends whether the key is established by one of the participants (and then transported to the other(s)) or agreed among the participants, and on the underlying cryptographic mechanisms (symmetric or asymmetric). Clearly, the design of key establishment protocols for sensor networks must deal with different problems and challenges that do not exist in wired networks. To name a few, wireless links are particularly vulnerable to eavesdropping, and that sensor devices can be captured (and the secrets they contain can be compromised); in many upcoming wireless sensor networks, nodes cannot rely on the presence of an online trusted server (whereas most standardized authentication and key establishment protocols do rely on such a server).
In particular, we will consider five distributed group key establishment protocols. Each of these protocols applies a different algorithmic technique that makes it more suitable for (i) static sensor networks, (ii) sensor networks where nodes enter sleep mode (i.e. dynamic, with low rate of updates on the connectivity graph) and (iii) fully dynamic networks where nodes may even be mobile. On the other hand, the common factor for all five protocols is that they can be applied in dynamic groups (where members can be excluded or added) and provide forward and backward secrecy. All these protocols are based on the DiffieHellman key exchange algorithm and constitute natural extensions of it in the multiparty case.
Abstract: Typical sensor nodes are resource constrained devices containing user level applications, operating system components, and device drivers in a single address space, with no form of memory protection. A malicious user could easily capture a node and tamper the applications running, in order to perform different types of attacks. In this paper, we propose a remote live forensics protection architecture that prevents the execution of tampered software while alarming the owners of the sensors network. Using sandboxing to restrict application memory accesses within the address space and forensic techniques to validate the authenticity of the running applications we prevent malicious code from being executed while specifying the intrusion.
Abstract: We consider the problem of searching for a piece of
information in a fully interconnected computer network
(also called a complete network or clique) by exploiting
advice about its location from the network nodes. Each
node contains a database that ?knows? what kind of
documents or information are stored in other nodes
(e.g., a node could be a Web server that answers queries
about documents stored on the Web). The databases in
each node, when queried, provide a pointer that leads to
the node that contains the information. However, this
information is uptodate (or correct) with some
bounded probability. While, in principle, one may always
locate the information by simply visiting the network
nodes in some prescribed ordering, this requires a time
complexity in the order of the number of nodes of the
network. In this paper, we provide algorithms for locating
an information node in the complete communication
network, which take advantage of advice given from
network nodes. The nodes may either give correct advice,
by pointing directly to the information node, or give
wrong advice, by pointing elsewhere. On the lowerbounds?
side, we show that no fixedmemory (i.e., with
memory independent of the network size) deterministic
algorithm may locate the information node in a constant
(independent of the network size) expected number of
steps. Moreover, if p (1/n) is the probability that a
node of an nnode clique gives correct advice, we show
that no algorithm may locate the information node in an
expected number of steps less than 1/p o(1). To study
how the expected number of steps is affected by the
amount of memory allowed to the algorithms, we give a
memoryless randomized algorithm with expected number
of steps 4/p o(1/p) o(1) and a 1bit randomized
algorithm requiring on the average at most 2/p o(1)
steps. In addition, in the memoryless case, we also
prove a 4/p lower bound for the expected number of
steps in the case where the nodes giving faulty advice
may decide on the content of this advice in any possible
way and not merely at random (adversarial fault model).
Finally, for the case where faulty nodes behave randomly,
we give an optimal, unlimited memory deterministic
algorithm with expected number of steps bounded
from above by 1/p o(1/p) 1.
Abstract: We consider the problem of searching for a piece of information in a fully interconnected computer network or clique by exploiting
advice about its location from the network nodes Each node contains a
database that knows what kind of documents or information are stored
in other nodes e.g. a node could be a Web server that answers queries
about documents stored on the Web. The databases in each node when
queried provide a pointer that leads to the node that contains the information. However this information is up to date or correct with some
bounded probability. While in principle one may always locate the information by simply visiting the network nodes in some prescribed ordering
this requires a time complexity in the order of the number of nodes of the
network. In this paper we provide algorithms for locating an information node in the complete communication network that take advantage
of advice given from network nodes The nodes may either give correct
advice by pointing directly to the information node or give wrong advice
by pointing elsewhere We show that on the averageif the probability that a node provides correct advice is asymptotically larger than
where is the number of the computer nodes then the average time complexity for locating the information node is asymptotically or depending on the available memory.The probability may in general be a function of the number of network nodes . On the lower bounds
side we prove that noxed memory deterministic algorithm can locate
the information node in nite expected number of steps. We also prove
a lower bound of
for the expected number of steps of any algorithm
that locates the information node in the complete network.
Abstract: In this paper we examine the problem of searching for some information item in the nodes of a fully
interconnected computer network, where each node contains information relevant to some topic
as well as links to other network nodes that also contain information, not necessarily related to
locally kept information. These links are used to facilitate the Internet users and mobile software
agents that try to locate specific pieces of information. However, the links do not necessarily point
to nodes containing information of interest to the user or relevant to the aims of the mobile agent.
Thus an element of uncertainty is introduced. For example, when an Internet user or some search
agent lands on a particular network node, they see a set of links that point to information that is,
supposedly, relevant to the current search. Therefore, we can assume that a link points to relevant
information with some unknown probability p that, in general, is related to the number of nodes
in the network (intuitively, as the network grows, this probability tends to zero since adding more
nodes to the network renders some extant links less accurate or obsolete). Consequently, since there
is uncertainty as to whether the links contained in a node?s Web page are correct or not, a search
algorithm cannot rely on following the links systematically since it may end up spending too much
time visiting nodes that contain irrelevant information. In this work, we will describe and analyze
a search algorithm that is only allowed to transfer a fixed amount of memory along communication
links as it visits the network nodes. The algorithm is, however, allowed to use one bit of memory at
each node as an ?already visited? flag. In this way the algorithm has its memory distributed to the
network nodes, avoiding overloading the network links as it moves from node to node searching for
the information. We work on fully interconnected networks for simplicity reasons and, moreover,
because according to some recent experimental evidence, such networks can be considered to be a
good approximation of the current structure of the World Wide Web.
Abstract: The promises inherent in users coming together to form data
sharing network communities, bring to the foreground new problems formulated
over such dynamic, ever growing, computing, storage, and networking
infrastructures. A key open challenge is to harness these highly
distributed resources toward the development of an ultra scalable, efficient
search engine. From a technical viewpoint, any acceptable solution
must fully exploit all available resources dictating the removal of any
centralized points of control, which can also readily lead to performance
bottlenecks and reliability/availability problems. Equally importantly,
however, a highly distributed solution can also facilitate pluralism in informing
users about internet content, which is crucial in order to preclude
the formation of informationresource monopolies and the biased visibility
of content from economicallypowerful sources. To meet these challenges,
the work described here puts forward MINERVA{\^a}{\"i}¿½{\"i}¿½, a novel search
engine architecture, designed for scalability and efficiency. MINERVA{\^a}{\"i}¿½{\"i}¿½
encompasses a suite of novel algorithms, including algorithms for creating
data networks of interest, placing data on network nodes, load balancing,
topk algorithms for retrieving data at query time, and replication algorithms
for expediting topk query processing. We have implemented the
proposed architecture and we report on our extensive experiments with
realworld, webcrawled, and synthetic data and queries, showcasing the
scalability and efficiency traits of MINERVA{\^a}{\"i}¿½{\"i}¿½.
Abstract: We present here, Fun in Numbers, a framework for developing multiplayer pervasive games that rely on the use of ad hoc mobile sensor networks. The unique feature in such games is that players interact with each other and their surrounding environment by using movement and presence as a means of performing gamerelated actions, utilizing sensor devices. We present the fundamental issues and challenges related to these type of games and the scenarios associated with them is provided. Our framework is developed using Java and is based on a multilayer architecture, which provides developers with a set of templates and services for building and operating new games. Our framework handles a number of challenging fundamental and practical issues, such as synchronization, network congestion, delaytolerant communication and neighbors discovery. We also present our platform and identify issues that arise in pervasive games which utilize sensor network nodes. The implemented games show how to use nonconventional user interface methods to breathe new life into familiar concepts, like the multiplayer games played out in open space.
Abstract: In this paper we propose an energyaware broadcast algorithm for wireless networks. Our algorithm is based on the multicost approach and selects the set of nodes that by transmitting implement broadcasting in an optimally energyefficient way. The energyrelated parameters taken into account are the node transmission power and the node residual energy. The algorithm{\^a}€™s complexity however is nonpolynomial, and therefore, we propose a relaxation producing a nearoptimal solution in polynomial time. We also consider a distributed information exchange scheme that can be coupled with the proposed algorithms and examine the overhead introduced by this integration. Using simulations we show that the proposed algorithms outperform other solutions in the literature in terms of energy efficiency. Moreover, it is shown that the nearoptimal algorithm obtains most of the performance benefits of the optimal algorithm at a smaller computational overhead.
Abstract: We propose a class of novel energyefficient multicost routing algorithms for wireless mesh networks, and evaluate their performance. In multicost routing, a vector of cost parameters is assigned to each network link, from which the cost vectors of candidate paths are calculated using appropriate operators. In the end these parameters are combined in various optimization functions, corresponding to different routing algorithms, for selecting the optimal path. We evaluate the performance of the proposed energyaware multicost routing algorithms under two models. In the network evacuation model, the network starts with a number of packets that have to be transmitted and an amount of energy per node, and the objective is to serve the packets in the smallest number of steps, or serve as many packets as possible before the energy is depleted. In the dynamic onetoone communication model, new data packets are generated continuously and nodes are capable of recharging their energy periodically, over an infinite time horizon, and we are interested in the maximum achievable steadystate throughput, the packet delay, and the energy consumption. Our results show that energyaware multicost routing increases the lifetime of the network and achieves better overall network performance than other approaches.
Abstract: In this work we study the combination of
multicost routing and adjustable transmission power
in wireless adhoc networks, so as to obtain dynamic
energy and interferenceefficient routes to optimize network performance. In multicost routing, a vector of
cost parameters is assigned to each network link, from
which the cost vectors of candidate paths are calcu
lated. Only at the end are these parameters combined in
various optimization functions, corresponding to different routing algorithms, for selecting the optimal path.
The multicost routing problem is a generalization of
the multiconstrained problem, where no constraints exist, and is also significantly more powerful than single
cost routing. Since energy is an important limitation of
wireless communications, the cost parameters consid
ered are the number of hops, the interference caused,
the residual energy and the transmission power of the
nodes on the path; other parameters could also be in
cluded, as desired.We assume that nodes can use power
control to adjust their transmission power to the desired
level. The experiments conducted show that the com
bination of multicost routing and adjustable transmis sion power can lead to reduced interference and energy
consumption, improving network performance and life
time.
Abstract: In this work we study the dynamic onetoone communica
tion problem in energy and capacityconstrained wireless adhoc net
works. The performance of such networks is evaluated under random
traﬃc generation and continuous energy recharging at the nodes over an
inﬁnitetime horizon.We are interested in the maximum throughput that
can be sustained by the network with the node queues being ﬁnite and in
the average packet delay for a given throughput. We propose a multicost
energyaware routing algorithm and compare its performance to that of
minimumhop routing. The results of our experiments show that gener
ally the energyaware algorithm achieves a higher maximum throughput
than the minimumhop algorithm. More speciﬁcally, when the network
is mainly energyconstrained and for the 2dimensional topology consid
ered, the throughput of the proposed energyaware routing algorithm is
found to be almost twice that of the minimumhop algorithm.
Abstract: In this work, we study the fundamental naming and counting problems (and some variations) in networks that are anonymous, unknown, and possibly dynamic. In counting, nodes must determine the size of the network n and in naming they must end up with unique identities. By anonymous we mean that all nodes begin from identical states
apart possibly from a unique leader node and by unknown that nodes
have no a priori knowledge of the network (apart from some minimal
knowledge when necessary) including ignorance of n. Network dynamicity is modeled by the 1interval connectivity model [KLO10], in which communication is synchronous and a (worstcase) adversary chooses the edges of every round subject to the condition that each instance is connected. We first focus on static networks with broadcast where we prove that, without a leader, counting is impossible to solve and that naming is impossible to solve even with a leader and even if nodes know n. These impossibilities carry over to dynamic networks as well. We also show that a unique leader suffices in order to solve counting in linear time.
Then we focus on dynamic networks with broadcast. We conjecture that
dynamicity renders nontrivial computation impossible. In view of this,
we let the nodes know an upper bound on the maximum degree that will
ever appear and show that in this case the nodes can obtain an upper
bound on n. Finally, we replace broadcast with onetoeach, in which a
node may send a different message to each of its neighbors. Interestingly,
this natural variation is proved to be computationally equivalent to a
fullknowledge model, in which unique names exist and the size of the
network is known.
Abstract: Evolutionary dynamics have been traditionally studied in the context of homogeneous populations, mainly described by the Moran process [15]. Recently, this approach has been generalized in [13] by arranging individuals on the nodes of a network (in general, directed). In this setting, the existence of directed arcs enables the simulation of extreme phenomena, where the fixation probability of a randomly placed mutant (i.e. the probability that the offsprings of the mutant eventually spread over the whole population) is arbitrarily small or large. On the other hand, undirected networks (i.e. undirected graphs) seem to have a smoother behavior, and thus it is more challenging to find suppressors/amplifiers of selection, that is, graphs with smaller/greater fixation probability than the complete graph (i.e. the homogeneous population). In this paper we focus on undirected graphs. We present the first class of undirected graphs which act as suppressors of selection, by achieving a fixation probability that is at most one half of that of the complete graph, as the number of vertices increases. Moreover, we provide some generic upper and lower bounds for the fixation
probability of general undirected graphs. As our main contribution, we introduce the natural alternative of the model proposed in [13]. In our new evolutionary model, all individuals interact simultaneously and the result is a compromise between aggressive and nonaggressive individuals. That is, the behavior of the individuals in our new model and in the model of [13] can be interpreted as an “aggregation” vs. an “allornothing” strategy, respectively. We prove that our new model of mutual influences admits a potential function, which guarantees the convergence of the system for any graph topology and any initial fitness vector of the individuals. Furthermore, we prove fast convergence to the stable state for the case of the complete graph, as well as we provide almost tight bounds on the limit fitness of the individuals. Apart from being important on its own, this new evolutionary model appears to be useful also in the abstract modeling of control mechanisms over invading populations in networks. We demonstrate this by introducing and analyzing two alternative control approaches, for which we bound the time needed to stabilize to the “healthy” state of the system.
Abstract: We propose new burst assembly schemes and fast reservation (FR) protocols for Optical Burst Switched (OBS) networks that are based on traffic prediction. The burst assembly schemes aim at minimizing (for a given burst size) the average delay of the packets incurred during the burst assembly process, while the fast reservation protocols aim at further reducing the endtoend delay of the data bursts. The burst assembly techniques use a linear prediction filter to estimate the number of packet arrivals at the ingress node in the following interval, and launch a new burst into the network when a certain criterion, different for each proposed scheme, is met. The fast reservation protocols use prediction filters to estimate the expected length of the burst and the time needed for the burst assembly process to complete. A Burst Header Packet (BHP) packet carrying these estimates is sent before the burst is completed, in order to reserve bandwidth at intermediate nodes for the time interval the burst is expected to pass from these nodes. Reducing the packet aggregation delay and the time required to perform the reservations, reduces the total time needed for a packet to be transported over an OBS network and is especially important for realtime applications. We evaluate the performance of the proposed burst assembly schemes and show that a number of them outperform the previously proposed timerbased, lengthbased and average delaybased burst assembly schemes. We also look at the performance of the fast reservation (FR) protocols in terms of the probability of successfully establishing the reservations required to transport the burst.
Abstract: We propose new burst assembly techniques that aim at reducing the average delay experienced by the packets during the burstification process in optical burst switched (OBS) networks, for a given average size of the bursts produced. These techniques use a linear prediction filter to estimate the number of packet arrivals at the ingress node in the following interval, and launch a new burst into the network when a certain criterion, which is different for each proposed scheme, is met. Reducing the packet burstification delay, for a given average burst size, is essential for realtime applications; correspondingly, increasing the average burst size for a given packet burstification delay is important for reducing the number of bursts injected into the network and the associated overhead imposed on the core nodes. We evaluate the performance of the proposed schemes and show that two of them outperform the previously proposed timer  based, length  based and average delaybased burst aggregation schemes in terms of the average packet burstification delay for a given average burst size.
Abstract: Wireless Sensor Networks (WSNs) constitute a recent and promising new
technology that is widely applicable. Due to the applicability of this
technology and its obvious importance for the modern distributed
computational world, the formal scientific foundation of its inherent laws
becomes essential. As a result, many new computational models for WSNs
have been proposed. Population Protocols (PPs) are a special category of
such systems. These are mainly identified by three distinctive
characteristics: the sensor nodes (agents) move passively, that is, they
cannot control the underlying mobility pattern, the available memory to
each agent is restricted, and the agents interact in pairs. It has been
proven that a predicate is computable by the PP model iff it is
semilinear. The class of semilinear predicates is a fairly small class. In
this work, our basic goal is to enhance the PP model in order to improve
the computational power. We first make the assumption that not only the
nodes but also the edges of the communication graph can store restricted
states. In a complete graph of n nodes it is like having added O(n2)
additional memory cells which are only read and written by the endpoints
of the corresponding edge. We prove that the new model, called Mediated
Population Protocol model, can operate as a distributed nondeterministic
Turing machine (TM) that uses all the available memory. The only
difference from a usual TM is that this one computes only symmetric
languages. More formally, we establish that a predicate is computable by
the new model iff it is symmetric and belongs to NSPACE(n2). Moreover, we
study the ability of the new model to decide graph languages (for general
graphs). The next step is to ignore the states of the edges and provide
another enhancement straight away from the PP model. The assumption now is
that the agents are multitape TMs equipped with infinite memory, that can
perform internal computation and interact with other agents, and we define
spacebounded computations. We call this the Passively mobile Machines
model. We prove that if each agent uses at most f(n) memory for f(n)={\`U}(log
n) then a predicate is computable iff it is symmetric and belongs to
NSPACE(nf(n)). We also show that this is not the case for f(n)=o(log n).
Based on these, we show that for f(n)={\`U}(log n) there exists a space
hierarchy like the one for classical symmetric TMs. We also show that the
latter is not the case for f(n)=o(loglog n), since here the corresponding
class collapses in the class of semilinear predicates and finally that for
f(n)={\`U}(loglog n) the class becomes a proper superset of semilinear
predicates. We leave open the problem of characterizing the classes for
f(n)={\`U}(loglog n) and f(n)=o(log n).
Abstract: Web services are becoming an important enabler of the Semantic Web. Besides the need for a rich description mechanism, Web Service information should be made available in an accessible way for machine processing. In this paper, we propose a new P2P basedapproach for Web Services discovery. Peers that store Web Services information, such as data item descriptions, are efficiently located using a scalable and robust data indexing structure for PeertoPeer data networks, NIPPERS. We present a theoretical analysis which shows that the communication cost of the query and update operations scale doublelogarithmically with the number of NIPPERS nodes. Furthermore, we show that the network is robust with respect to failures fulfilling quality of web services requirements.
Abstract: We investigate the practical merits of a parallel priority queue
through its use in the development of a fast and workefficient parallel
shortest path algorithm, originally designed for an EREW PRAM. Our
study reveals that an efficient implementation on a real supercomputer
requires considerable effort to reduce the communication performance
(which in theory is assumed to take constant time). It turns out that the
most crucial part of the implementation is the mapping of the logical
processors to the physical processing nodes of the supercomputer. We
achieve the requested efficient mapping through a new graphtheoretic
result of independent interest: computing a Hamiltonian cycle on a directed
hypertorus. No such algorithm was known before for the case of
directed hypertori. Our Hamiltonian cycle algorithm allows us to considerably
improve the communication cost and thus the overall performance
of our implementation.
Abstract: We study network connection games where the nodes of a networ
k perform edge swaps
in order to improve their communication costs. For the model
proposed by [2], in which the selfish
cost of a node is the sum of all shortest path distances to the o
ther nodes, we use the probabilistic
method to provide a new, structural characterization of equ
ilibrium graphs. We show how to use this
characterization in order to prove upper bounds on the diame
ter of equilibrium graphs in terms of the
size of the largest
k
vicinity (defined as the the set of vertices within distance
k
from a vertex), for
any
k
≥
1 and in terms of the number of edges, thus settling positivel
y a conjecture of [2] in the cases
of graphs of large
k
vicinity size (including graphs of large maximum degree) a
nd of graphs which are
dense enough.
Next, we present a new swapbased network creation game, in w
hich selfish costs depend on the imme
diate neighborhood of each node; in particular, the profit of
a node is defined as the sum of the degrees
of its neighbors. We prove that, in contrast to the previous m
odel, this network creation game admits
an exact potential, and also that any equilibrium graph cont
ains an induced star. The existence of the
potential function is exploited in order to show that an equi
librium can be reached in expected polyno
mial time even in the case where nodes can only acquire limite
d knowledge concerning nonneighboring
nodes.
Abstract: In this paper we propose an energyefficient broadcast algorithm for wireless networks for the case where the transmission powers of the nodes are fixed. Our algorithm is based on the multicost approach and selects an optimal energyefficient set of nodes for broadcasting, taking into account: i) the node residual energies, ii) the transmission powers used by the nodes, and iii) the set of nodes that are covered by a specific schedule. Our algorithm is optimal, in the sense that it can optimize any desired function of the total power consumed by the broadcasting task and the minimum of the current residual energies of the nodes, provided that the optimization function is monotonic in each of these parameters. Our algorithm has nonpolynomial complexity, thus, we propose a relaxation producing a nearoptimal solution in polynomial time. Using simulations we show that the proposed algorithms outperform other established solutions for energyaware broadcasting with respect to both energy consumption and network lifetime. Moreover, it is shown that the nearoptimal multicost algorithm obtains most of the performance benefits of the optimal multicost algorithm at a smaller computational overhead.
Abstract: This paper studies the data gathering problem in wireless networks, where data generated at the nodes has to be collected at a single sink. We investigate the relationship between routing optimality and fair resource management. In particular, we prove that for energy balanced data propagation, Pareto optimal routing and flow maximization are equivalent, and also prove that flow maximization is equivalent to maximizing the network lifetime. We algebraically characterize the network structures in which energy balanced data flows are maximal. Moreover, we algebraically characterize communication links which are not used by an optimal flow. This leads to the characterization of minimal network structures supporting the maximal flows.
We note that energy balance, although implying global optimality, is a local property that can be computed efficiently and in a distributed manner. We suggest online distributed algorithms for energy balance in different optimal network structures and numerically show their stability in particular setting. We remark that although the results obtained in this paper have a direct consequence in energy saving for wireless networks they do not limit themselves to this type of networks neither to energy as a resource. As a matter of fact, the results are much more general and can be used for any type of network and different type of resources.
Abstract: This paper studies the data gathering problem in wireless networks, where data generated at the nodes has to be collected at a single sink. We investigate the relationship between routing optimality and fair resource management. In particular, we prove that for energybalanced data propagation, Pareto optimal routing and flow maximization are equivalent, and also prove that flow maximization is equivalent to maximizing the network lifetime. We algebraically characterize the network structures in which energybalanced data flows are maximal. Moreover, we algebraically characterize communication links which are not used by an optimal flow. This leads to the characterization of minimal network structures supporting the maximal flows.
We note that energybalance, although implying global optimality, is a local property that can be computed efficiently and in a distributed manner. We suggest online distributed algorithms for energybalance in different optimal network structures and numerically show their stability in particular setting. We remark that although the results obtained in this paper have a direct consequence in energy saving for wireless networks they do not limit themselves to this type of networks neither to energy as a resource. As a matter of fact, the results are much more general and can be used for any type of network and different types of resources.
Abstract: In this work, we study the impact of dynamically changing link capacities on the delay bounds of LIS (LongestInSystem) and SIS (ShortestInSystem) protocols on specific networks (that can be modelled as Directed Acyclic Graphs (DAGs)) and stability bounds of greedy contention–resolution protocols running on arbitrary networks under the Adversarial Queueing Theory. Especially, we consider the model of dynamic capacities, where each link capacity may take on integer values from [1,C] with C>1, under a (w,\~{n})adversary. We show that the packet delay on DAGs for LIS is upper bounded by O(iw\~{n}C) and lower bounded by {\`U}(iw\~{n}C) where i is the level of a node in a DAG (the length of the longest path leading to node v when nodes are ordered by the topological order induced by the graph). In a similar way, we show that the performance of SIS on DAGs is lower bounded by {\`U}(iw\~{n}C), while the existence of a polynomial upper bound for packet delay on DAGs when SIS is used for contention–resolution remains an open problem. We prove that every queueing network running a greedy contention–resolution protocol is stable for a rate not exceeding a particular stability threshold, depending on C and the length of the longest path in the network.
Abstract: In this work we extend the population protocol model of Angluin et al., in
order to model more powerful networks of very small resource limited
artefacts (agents) that is possible to follow some unpredictable passive
movement. These agents communicate in pairs according to the commands of
an adversary scheduler. A directed (or undirected) communication graph
encodes the following information: each edge (u,\~{o}) denotes that during the
computation it is possible for an interaction between u and \~{o} to happen in
which u is the initiator and \~{o} the responder. The new characteristic of
the proposed mediated population protocol model is the existance of a
passive communication provider that we call mediator. The mediator is a
simple database with communication capabilities. Its main purpose is to
maintain the permissible interactions in communication classes, whose
number is constant and independent of the population size. For this reason
we assume that each agent has a unique identifier for whose existence the
agent itself is not informed and thus cannot store it in its working
memory. When two agents are about to interact they send their ids to the
mediator. The mediator searches for that ordered pair in its database and
if it exists in some communication class it sends back to the agents the
state corresponding to that class. If this interaction is not permitted to
the agents, or, in other words, if this specific pair does not exist in
the database, the agents are informed to abord the interaction. Note that
in this manner for the first time we obtain some control on the safety of
the network and moreover the mediator provides us at any time with the
network topology. Equivalently, we can model the mediator by communication
links that are capable of keeping states from a edge state set of constant
cardinality. This alternative way of thinking of the new model has many
advantages concerning the formal modeling and the design of protocols,
since it enables us to abstract away the implementation details of the
mediator. Moreover, we extend further the new model by allowing the edges
to keep readable only costs, whose values also belong to a constant size
set. We then allow the protocol rules for pairwise interactions to modify
the corresponding edge state by also taking into account the costs. Thus,
our protocol descriptions are still independent of the population size and
do not use agent ids, i.e. they preserve scalability, uniformity and
anonymity. The proposed Mediated Population Protocols (MPP) can stably
compute graph properties of the communication graph. We show this for the
properties of maximal matchings (in undirected communication graphs), also
for finding the transitive closure of directed graphs and for finding all
edges of small cost. We demonstrate that our mediated protocols are
stronger than the classical population protocols. First of all we notice
an obvious fact: the classical model is a special case of the new model,
that is, the new model can compute at least the same things with the
classical one. We then present a mediated protocol that stably computes
the product of two nonnegative integers in the case where G is complete
directed and connected. Such kind of predicates are not semilinear and it
has been proven that classical population protocols in complete graphs can
compute precisely the semilinear predicates, thus in this manner we show
that there is at least one predicate that our model computes and which the
classical model cannot compute. To show this fact, we state and prove a
general Theorem about the composition of two mediated population
protocols, where the first one has stabilizing inputs. We also show that
all predicates stably computable in our model are (nonuniformly) in the
class NSPACE(m), where m is the number of edges of the communication
graph. Finally, we define Randomized MPP and show that, any Peano
predicate accepted by a Randomized MPP, can be verified in deterministic
polynomial time.
Abstract: In this paper we study the problem of assigning transmission ranges to the nodes of a multihop
packet radio network so as to minimize the total power consumed under the constraint
that adequate power is provided to the nodes to ensure that the network is strongly connected
(i.e., each node can communicate along some path in the network to every other node). Such
assignment of transmission ranges is called complete. We also consider the problem of achieving
strongly connected bounded diameter networks.
For the case of n + 1 colinear points at unit distance apart (the unit chain) we give a tight
asymptotic bound for the minimum cost of a range assignment of diameter h when h is a xed
constant and when h>(1 + ) log n, for some constant > 0. When the distances between the
colinear points are arbitrary, we give an O(n4) time dynamic programming algorithm for nding
a minimum cost complete range assignment.
For points in three dimensions we show that the problem of deciding whether a complete
range assignment of a given cost exists, is NPhard. For the same problem we give an O(n2)
time approximation algorithm which provides a complete range assignment with cost within a
factor of two of the minimum. The complexity of this problem in two dimensions remains open,
while the approximation algorithm works in this case as well.
Abstract: The sensor devices are battery powered thus energy is the most precious resource of a wireless sensor
network since periodically replacing the battery of the nodes in large scale deployments is infeasible. The
collected data is disseminated to a static control point { data sink in the network, using node to node
{ multihop data propagation, [4, 6]. However, sensor devices consume signicant amounts of energy in
addition to increased implementation complexity since a routing protocol is executed. Also, a point of
failure emerges in the area near the control center where nodes relay the data from nodes that are farther
away
Abstract: In this work we address the issue of efficient processing of range queries in DHTbased P2P data networks. The novelty of the proposed approach lies on architectures, algorithms, and mechanisms for identifying and appropriately exploiting powerful nodes in such networks. The existence of such nodes has been well documented in the literature and plays a key role in the architecture of most successful realworld P2P applications. However, till now, this heterogeneity has not been taken into account when architecting solutions for complex query processing, especially in DHT networks. With this work we attempt to fill this gap for optimizing the processing of range queries. Significant performance improvements are achieved due to (i) ensuring a much smaller hop count performance for range queries, and (ii) avoiding the dangers and inefficiencies of relying for range query processing on weak nodes, with respect to processing, storage, and communication capacities, and with intermittent connectivity. We present detailed experimental results validating our performance claims.
Abstract: Data propagation in wireless sensor
networks is usually performed as a multihop process.
Thus,
To deliver a single
message, the resources of many sensor nodes are used and
a lot of energy is spent.
Recently, a novel approach is catching momentum because of important applications;
that of having a mobile sink move inside the network area and collect
the data with low energy cost.
Here we extend this line of research by proposing and evaluating three new protocols.
Our protocols are novel in
a) investigating the impact of having {many} mobile sinks
b) in weak models with restricted mobility, proposing and evaluating
a mix of static and mobile sinks and c) proposing a distributed
protocol that tends to {equally spread the sinks} in the network to
further improve performance.
Our protocols are simple, based on randomization and assume locally
obtainable information. We perform an extensive evaluation via simulation; our
findings demonstrate that our solutions scale very well with respect to the number of sinks
and significantly reduce energy consumption and delivery delay.
Abstract: We consider information aggregation as a method for reducing the information exchanged in a Grid network and used by the resource manager in order to make scheduling decisions. In this way, information is summarized across nodes and sensitive or detailed information can be kept private, while resources are still publicly available for use. We present a general framework for information aggregation, trying to identify issues that relate to aggregation in Grids. In this context, we describe a number of techniques, including single point and intradomain aggregation, define appropriate gridspecific domination relations and operators for aggregating static and dynamic resource information, and discuss resource selection optimization functions. The quality of an aggregation scheme is measured both by its effects on the efficiency of the scheduler¢s decisions and also by the reduction it brings on the amount of resource information recorded, a tradeoff that we examine in detail. Simulation experiments demonstrate that the proposed schemes achieve significant information reduction, either in the amount of information exchanged, or in the frequency of the updates, while at the same time maintaining most of the value of the original information as expressed by a stretch factor metric we introduce.
Abstract: In this work we tackle the open problem of selfjoin size (SJS) estimation in a largescale distributed data system, where tuples of a relation are distributed over data nodes which comprise an overlay network. Our contributions include adaptations of five wellknown SJS estimation centralized techniques (coined sequential, crosssampling, adaptive, bifocal, and samplecount) to the network environment and a novel technique which is based on the use of the Gini coefficient. We develop analyses showing how Gini estimations can lead to estimations of the underlying Zipfian or powerlaw value distributions. We further contribute distributed sampling algorithms that can estimate accurately and efficiently the Gini coefficient. Finally, we provide detailed experimental evidence testifying for the claimed increased accuracy, precision, and efficiency of the proposed SJS estimation method, compared to the other methods. The proposed approach is the only one to ensure high efficiency, precision, and accuracy regardless of the skew of the underlying data.
Abstract: Our position is that a key to research efforts on ensuring high
performance in very large scale sharing networks is the idea of
volunteering; recognizing that such networks are comprised of
largely heterogeneous nodes in terms of their capacity and
behaviour, and that, in many realworld manifestations, a few
nodes carry the bulk of the request service load. In this paper we
outline how we employ volunteering as the basic idea using
which we develop altruismendowed selforganizing sharing
networks to help solve two open problems in largescale peertopeer
networks: (i) to develop an overlay topology structure that
enjoys better performance than DHTstructured networks and,
specifically, to offer O(log log N) routing performance in a
network of N nodes, instead of O(log N), and (ii) to efficiently
process complex queries and range queries, in particular.
Abstract: In this work, we study protocols so that populations of distributed processes can construct networks. In order to highlight the basic principles of distributed network construction, we keep the model minimal in all respects. In particular, we assume finitestate processes that all begin from the same initial state and all execute the same protocol. Moreover, we assume pairwise interactions between the processes that are scheduled by a fair adversary. In order to allow processes to construct networks, we let them activate and deactivate their pairwise connections. When two processes interact, the protocol takes as input the states of the processes and the state of their connection and updates all of them. Initially all connections are inactive and the goal is for the processes, after interacting and activating/deactivating connections for a while, to end up with a desired stable network. We give protocols (optimal in some cases) and lower bounds for several basic network construction problems such as spanning line, spanning ring, spanning star, and regular network. The expected time to convergence of our protocols is analyzed under a uniform random scheduler. Finally, we prove several universality results by presenting generic protocols that are capable of simulating a Turing Machine (TM) and exploiting it in order to construct a large class of networks. We additionally show how to partition the population into k supernodes, each being a line of log k nodes, for the largest such k. This amount of local memory is sufficient for the supernodes to obtain unique names and exploit their names and their memory to realize nontrivial constructions.
Abstract: In this work, we study protocols (i.e. distributed algorithms) so that populations of distributed processes can construct networks. In order to highlight the basic principles of distributed network construction we keep the model minimal in all respects. In particular, we assume finitestate processes that all begin from the same initial state and all execute the same protocol (i.e. the system is homogeneous). Moreover, we assume pairwise interactions between the processes that are scheduled by an adversary. The only constraint on the adversary scheduler is that it must be fair, intuitively meaning that it must assign to every reachable configuration of the system a nonzero probability to occur. In order to allow processes to construct networks, we let them activate and deactivate their pairwise connections. When two processes interact, the protocol takes as input the states of the processes and the state of their connection and updates all of them. In particular, in every interaction, the protocol may activate an inactive connection, deactivate an active one, or leave the state of a connection unchanged. Initially all connections are inactive and the goal is for the processes, after interacting and activating/deactivating connections for a while, to end up with a desired stable network (i.e. one that does not change any more). We give protocols (optimal in some cases) and lower bounds for several basic network construction problems such as spanning line, spanning ring, spanning star, and regular network. We provide proofs of correctness for all of our protocols and analyze the expected time to convergence of most of them under a uniform random scheduler that selects the next pair of interacting processes uniformly at random from all such pairs. Finally, we prove several universality results by presenting generic protocols that are capable of simulating a Turing Machine (TM) and exploiting it in order to construct a large class of networks. Our universality protocols use a subset of the population (waste) in order to distributedly construct there a TM able to decide a graph class in some given space. Then, the protocols repeatedly construct in the rest of the population (useful space) a graph equiprobably drawn from all possible graphs. The TM works on this and accepts if the presented graph is in the class. We additionally show how to partition the population into k supernodes, each being a line of log k nodes, for the largest such k. This amount of local memory is sufficient for the supernodes to obtain unique names and exploit their names and their memory to realize nontrivial constructions. Delicate composition and reinitialization issues have to be solved for these general constructions to work.
Abstract: One of the most eminent problems in sensor networks is the
routing of data to a central destination in a robust and e±cient manner.
In this work we propose a new scalable protocol for propagating infor
mation about a sensed event towards a receiving center. Using only local
information and total absence of coordination between sensors our pro
tocol achieves to propagate the sensed data to a receiving center by ac
tivating only those nodes that lie very close to the optimal path between
the source of the event and the destination, resulting in low activation of
the network's sensors. Thus the protocol is very energy e±cient. Further
more, our protocol is robust as it manages to propagate the information
even when sensors fail with certain probability.
Abstract: In emerging pervasive scenarios, data is collected by sensing devices in streams that occur at several distributed points of observation. The size of the data typically far exceeds the storage and computational capabilities of the tiny devices that have to collect and process them. A general and challenging task is to allow (some of) the nodes of a pervasive network to collectively perform monitoring of a neighbourhood of interest by issuing continuous aggregate queries on the streams observed in its vicinity. This class of algorithms is fully decentralized and diffusive in nature: collecting all the data at a few central nodes of the network is unfeasible in networks of low capability devices or in the presence of massive data sets. Two main problems arise in this scenario: (i) the intrinsic complexity of maintaining statistics over a data stream whose size greatly exceeds the capabilities of the device that performs the computation; (ii) composing the partial outcomes computed at different points of observation into an accurate, global statistic over a neighbourhood of interest, which entails coping with several problems, last but not least the receipt of duplicate information along multiple paths of diffusion.
Streaming techniques have emerged as powerful tools to achieve the general goals described above, in the first place because they assume a computational model in which computational and storage resources are assumed to be far exceeded by the amount of data on which computation occurs. In this contribution, we review the main streaming techniques and provide a classification of the computational problems and the applications they effectively address, with an emphasis on decentralized scenarios, which are of particular interest in pervasive networks
Abstract: In this work, we consider a \emph{solution of automata} similar to \emph{Population Protocols} and \emph{Network Constructors}. The automata (also called \emph{nodes}) move passively in a wellmixed solution without being capable of controlling their movement. However, the nodes can \emph{cooperate} by interacting in pairs. Every such interaction may result in an update of the local states of the nodes. Additionally, the nodes may also choose to connect to each other in order to start forming some required structure. We may think of such nodes as the \emph{smallest possible programmable pieces of matter}, like tiny nanorobots or programmable molecules. The model that we introduce here is a more applied version of Network Constructors, imposing \emph{physical} (or \emph{geometrical}) \emph{constraints} on the connections that the nodes are allowed to form. Each node can connect to other nodes only via a very limited number of \emph{local ports}, which implies that at any given time it has only a \emph{bounded number of neighbors}. Connections are always made at \emph{unit distance} and are \emph{perpendicular to connections of neighboring ports}. Though such a model cannot form abstract networks like Network Constructors, it is still capable of forming very practical \emph{2D or 3D shapes}. We provide direct constructors for some basic shape construction problems, like \emph{spanning line}, \emph{spanning square}, and \emph{selfreplication}. We then develop \emph{new techniques} for determining the computational and constructive capabilities of our model. One of the main novelties of our approach, concerns our attempt to overcome the inability of such systems to detect termination. In particular, we exploit the assumptions that the system is wellmixed and has a unique leader, in order to \emph{give terminating protocols that are correct with high probability}. This allows us to develop terminating subroutines that can be \emph{sequentially composed} to form larger \emph{modular protocols} (which has not been the case in the relevant literature). One of our main results is a \emph{terminating protocol counting the size $n$ of the system} with high probability. We then use this protocol as a subroutine in order to develop our \emph{universal constructors}, establishing that \emph{it is possible for the nodes to become selforganized with high probability into arbitrarily complex shapes while still detecting termination of the construction}.
Abstract: We extend the population protocol model with a covertime service that informs a walking state every time it covers the whole network. This represents a known upper bound on the cover time of a random walk. The covertime service allows us to introduce termination into population protocols, a capability that is crucial for any distributed system. By reduction to an oraclemodel we arrive at a very satisfactory lower bound on the computational power of the model: we prove that it is at least as strong as a Turing Machine of space log n with input commutativity, where n is the number of nodes in the network. We also give a log nspace, but nondeterministic this time, upper bound. Finally, we prove interesting similarities of this model to linear bounded automata.
Abstract: We extend the population protocol model with a covertime service that informs a walking state every time it covers the whole network. This is simply a known upper bound on the cover time of a random walk. This allows us to introduce termination into population protocols, a capability that is crucial for any distributed system. By reduction to an oraclemodel we arrive at a very satisfactory lower bound on the computational power of the model: we prove that it is at least as strong as a Turing Machine of space logn with input commutativity, where n is the number of nodes in the network. We also give a lognspace, but nondeterministic this time, upper bound. Finally, we prove interesting similarities of this model to linear bounded automata.
Abstract: In this work, we discuss multiplayer pervasive
games that rely on the use of ad hoc mobile sensor networks.
The unique feature in such games is that players interact
with each other and their surrounding environment by using
movement and presence as a means of performing gamerelated
actions, utilizing sensor devices. We discuss the fundamental
issues and challenges related to these type of games and the
scenarios associated with them. We also present and evaluate
an example of such a game, called the “Hot Potato”, developed
using the Sun SPOT hardware platform. We provide a set of
experimental results, so as to both evaluate our implementation
and also to identify issues that arise in pervasive games which
utilize sensor network nodes, which show that there is great
potential in this type of games.
Abstract: Recent advances in the alloptical signal processing
domain report highspeed and nontrivial
functionality directly implemented in the optical
layer. These developments mean that the alloptical
processing of packet headers has a future.
In this article we address various important control
plane issues that must be resolved when
designing networks based on alloptical packetswitched
nodes.
Abstract: In this work, we study the impact of the dynamic changing of the network link capacities on the stability properties of packetswitched networks. Especially, we consider the Adversarial, QuasiStatic Queuing Theory model, where each link capacity may take on only two possible (integer) values, namely 1 and C>1 under a (w,\~{n})adversary. We obtain the following results:
• Allowing such dynamic changes to the link capacities of a network with just ten nodes that uses the LIS (LongestinSystem) protocol for contention–resolution results in instability at rates View the MathML source and for large enough values of C.
• The combination of dynamically changing link capacities with compositions of contention–resolution protocols on network queues suffices for similar instability bounds: The composition of LIS with any of SIS (ShortestinSystem), NTS (NearesttoSource), and FTG (FurthesttoGo) protocols is unstable at rates View the MathML source for large enough values of C.
• The instability bound of the network subgraphs that are forbidden for stability is affected by the dynamic changes to the link capacities: we present improved instability bounds for all the directed subgraphs that were known to be forbidden for stability on networks running a certain greedy protocol.
Abstract: Consider k particles, 1 red and k1 white, chasing each other on the nodes of a graph G. If the red one catches one of the white, it “infects” it with its color. The newly red particles are now available to infect more white ones. When is it the case that all white will become red? It turns out that this simple question is an instance of information propagation between random walks and has important applications to mobile computing where a set of mobile hosts acts as an intermediary for the spread of information.
In this paper we model this problem by k concurrent random walks, one corresponding to the red particle and k1 to the white ones. The infection time Tk of infecting all the white particles with red color is then a random variable that depends on k, the initial position of the particles, the number of nodes and edges of the graph, as well as on the structure of the graph.
In this work we develop a set of probabilistic tools that we use to obtain upper bounds on the (worst case w.r.t. initial positions of particles) expected value of Tk for general graphs and important special cases. We easily get that an upper bound on the expected value of Tk is the worst case (over all initial positions) expected meeting time m* of two random walks multiplied by . We demonstrate that this is, indeed, a tight bound; i.e. there is a graph G (a special case of the “lollipop” graph), a range of values k
Abstract: We consider a security problem on a distributed network.
We assume a network whose nodes are vulnerable to infection
by threats (e.g. viruses), the attackers. A system security
software, the defender, is available in the system. However,
due to the network¢s size, economic and performance reasons,
it is capable to provide safety, i.e. clean nodes from
the possible presence of attackers, only to a limited part of
it. The objective of the defender is to place itself in such a
way as to maximize the number of attackers caught, while
each attacker aims not to be caught.
In [7], a basic case of this problem was modeled as a
noncooperative game, called the Edge model. There, the
defender could protect a single link of the network. Here,
we consider a more general case of the problem where the
defender is able to scan and protect a set of k links of the
network, which we call the Tuple model. It is natural to expect
that this increased power of the defender should result
in a better quality of protection for the network. Ideally,
this would be achieved at little expense on the existence and
complexity of Nash equilibria (profiles where no entity can
improve its local objective unilaterally by switching placements
on the network).
In this paper we study pure and mixed Nash equilibria
in the model. In particular, we propose algorithms for computing
such equilibria in polynomial time and we provide a
polynomialtime transformation of a special class of Nash
equilibria, called matching equilibria, between the Edge
model and the Tuple model, and vice versa. Finally, we
establish that the increased power of the defender results in
higherquality protection of the network.
Abstract: We propose and evaluate the performance of a new MAClayer protocol for mobile ad hoc networks, called the Slow Start Power Controlled (abbreviated SSPC) protocol. SSPC improves on IEEE 802.11 by using power control for the RTS/CTS and DATA frame transmissions, so as to reduce energy consumption and increase network throughput and lifetime. In our scheme the transmission power used for the RTS frames is not constant, but follows a slow start principle. The CTS frames, which are sent at maximum transmission power, prevent the neighbouring nodes from transmitting their DATA frames at power levels higher than a computed threshold, while allowing them to transmit at power levels less than that threshold. Reduced energy consumption is achieved by adjusting the node transmission power to the minimum required value for reliable reception at the receiving node, while increase in network throughput is achieved by allowing more transmissions to take place simultaneously. The slow start principle used for calculating the appropriate DATA frames transmission power and the possibility of more simultaneous collisionfree transmissions differentiate the SSPC protocol from the other MAC solutions proposed for IEEE 802.11. Simulation results indicate that the SSPC protocol achieves a significant reduction in power consumption, average packet delay and frequency of RTS frame collisions, and a significant increase in network throughput and receivedtosent packets ratio compared to IEEE 802.11 protocol.
Abstract: We consider random systems of linear equations over GF(2) in which every equation binds k variables. We obtain a precise description of the clustering of solutions in such systems. In particular, we prove that with probability that tends to 1 as the number of variables, n, grows: for every pair of solutions \sigma, \tau, either there exists a sequence of solutions \sigma,...,\tau, in which successive elements differ by O(log n) variables, or every sequence of solutions \sigma,...,\tau, contains a step requiring the simultaneous change of \Omega(n) variables. Furthermore, we determine precisely which pairs of solutions are in each category. Our results are tight and highly quantitative in nature. Moreover, our proof highlights the role of unique extendability as the driving force behind the success of Low Density Parity Check codes and our techniques also apply to the problem of socalled pseudocodewords in such codes.
Abstract: In this paper we study the threshold behavior of the fixed radius random graph model and its applications to the key management problem of sensor networks and, generally, for mobile adhoc networks. We show that this random graph model can realistically model the placement of nodes within a certain region and their interaction/sensing capabilities (i.e. transmission range, light sensing sensitivity etc.). We also show that this model can be used to define key sets for the network nodes that satisfy a number of good properties, allowing to set up secure communication with each other depending on randomly created sets of keys related to their current location. Our work hopes to inaugurate a study of key management schemes whose properties are related to properties of an appropriate random graph model and, thus, use the rich theory developed in the random graph literature in order to transfer ?good? properties of the graph model to the key sets of the nodes.
Partially supported by the IST Programme of the European Union under contact number IST200515964 (AEOLUS) and the INTAS Programme under contract with Ref. No 04777173 (Data Flow Systems: Algorithms and Complexity (DFSAC)).
Abstract: Peertopeer sharing systems are becoming
increasingly popular and an exciting new class of
innovative, internetbased data management
systems. In these systems, users contribute their
own resources (processing units and storage
devices) and content (i.e., documents) to the P2P
community. We focus on the management of
content and resources in such systems. Our goal
is to harness all available resources in the P2P
network so that the users can access all available
content efficiently. Efficiency is taken both from
(i) the point of view of the system, in that we
strive to ensure fair load distribution among all
peer nodes, and (ii) from the point of view of the
users, in that we strive to ensure low userrequest
response times.
We propose a novel architecture for this new
class of applications, which differs drastically
from what is either found currently in existing
products or proposed in academia. We contribute
and study novel solutions that achieve our goals,
while at the same time addressing the formidable
challenges due to the autonomy of peers, their
heterogeneous processing and storage capacities,
their different content contributions, the huge
system scale, and the highly dynamic system
environment.
Abstract: In this work, we introduce the notion of time to some wellknown combinatorial optimization problems. In particular, we study problems defined on temporal graphs. A temporal graph D=(V,A) may be viewed as a timesequence G_1,G_2,...,G_l of static graphs over the same (static) set of nodes V. Each G_t = D(t) = (V,A(t)) is called the instance of D at time t and l is called the lifetime of D. Our main focus is on analogues of traveling salesman problems in temporal graphs. A sequence of timelabeled edges (e.g. a tour) is called temporal if its labels are strictly increasing. We begin by considering the problem of exploring the nodes of a temporal graph as soon as possible. In contrast to the positive results known for the static case, we prove that, it cannot be approximated within cn, for some constant c > 0, in general temporal graphs and within (2 − \varepsilon), for every constant \varepsilon > 0, in the special case in which D(t) is connected for all 1 <= t <= l, both unless P = NP. We then study the temporal analogue of TSP(1,2), abbreviated TTSP(1,2), where, for all 1 <= t <= l, D(t) is a complete weighted graph with edgecosts from {1,2} and the cost of an edge may vary from instance to instance. The goal is to find a minimum cost temporal TSP tour. We give several polynomialtime approximation algorithms for TTSP(1,2). Our best approximation is (1.7 + \varepsilon) for the generic TTSP(1,2) and (13/8 + \varepsilon) for its interesting special case in which the lifetime of the temporal graph is restricted to n. In the way, we also introduce temporal versions of Maximum Matching, Path Packing, MaxTSP, and Minimum Cycle Cover, for which we obtain polynomialtime approximation algorithms and hardness results.
Abstract: In this paper we present an overview of WISEBED, a largescale wireless sensor network testbed, which is currently being built for research purposes. This project is led by a number of European Universities
and Research Institutes, hoping to provide scientists, researchers and companies with an environment to conduct experiments with, in order to evaluate and validate their sensor networkrelated work. The initial planning of the project includes a large, heterogeneous testbed, consisting of at least 9 geographically disparate networks that include both sensor and actuator nodes, and scaling in the order of thousands (currently being in total 550 nodes).We present here the overall architecture
of WISEBED, focusing on certain aspects of the software ecosystem surrounding the project, such as the Open Federation Alliance, which will enable a view of the whole testbed, or parts of it, as single entities, and the testbed's tight integration with the Shawn network simulator. We also present examples of the actual hardware used currently in the testbed and outline the architecture of two of the testbed's sites.
Abstract: There exists a great amount of algorithms for wireless sensor networks (WSNs) that have never been tried in practice. This is due to the fact that programming sensor nodes still happens on a very technical level. We remedy the situation by introducing our algorithm library Wiselib, which allows for simple implementations of algorithms. It can adopt to a large variety of hardware and software. This is achieved by employing advanced C++ techniques such as templates and inline functions, which allow to write generic code that is resolved and bound at compile time, resulting in virtually no memory or computation overhead at run time. The Wiselib runs on different host operating systems such as Contiki, iSense OS, and ScatterWeb. Furthermore, it runs on virtual nodes simulated by Shawn. The Wiselib provides an algorithm with data structures that suit the specific properties of the target platform. Algorithm code does not contain any platformspecific specializations, allowing a single implementation to run natively on heterogeneous networks. In this paper, we describe the building blocks of the Wiselib, analyze the overhead, and show how cryptographically secured routing algorithms can be implemented. We also report on results from experiments with real sensor node hardware.