Abstract: Implementation of a commercial application to a
grid infrastructure introduces new challenges in managing the
quality-of-service (QoS) requirements, most stem from the fact
that negotiation on QoS between the user and the service provider
should strictly be satisfied. An interesting commercial application
with a wide impact on a variety of fields, which can benefit from
the computational grid technologies, is three–dimensional (3-D)
rendering. In order to implement, however, 3-D rendering to a
grid infrastructure, we should develop appropriate scheduling
and resource allocation mechanisms so that the negotiated (QoS)
requirements are met. Efficient scheduling schemes require
modeling and prediction of rendering workload. In this paper
workload prediction is addressed based on a combined fuzzy
classification and neural network model. Initially, appropriate
descriptors are extracted to represent the synthetic world. The
descriptors are obtained by parsing RIB formatted files, which
provides a general structure for describing computer-generated
images. Fuzzy classification is used for organizing rendering
descriptor so that a reliable representation is accomplished which
increases the prediction accuracy. Neural network performs
workload prediction by modeling the nonlinear input-output
relationship between rendering descriptors and the respective
computational complexity. To increase prediction accuracy, a
constructive algorithm is adopted in this paper to train the neural
network so that network weights and size are simultaneously
estimated. Then, a grid scheduler scheme is proposed to estimate
the queuing order that the tasks should be executed and the
most appopriate processor assignment so that the demanded
QoS are satisfied as much as possible. A fair scheduling policy is
considered as the most appropriate. Experimental results on a real
grid infrastructure are presented to illustrate the efficiency of the
proposed workload prediction — scheduling algorithm compared
to other approaches presented in the literature.
Abstract: We propose a simple obstacle model to be used while simulating wireless sensor networks. To the best of our knowledge, this is the first time such an integrated and systematic obstacle model for these networks has been proposed. We define several types of obstacles that can be found inside the deployment area of a wireless sensor network and provide a categorization of these obstacles based on their nature (physical and communication obstacles, i.e. obstacles that are formed out of node distribution patterns or have physical presence, respectively), their shape and their change of nature over time. We make an eXtension to a custom-made sensor network simulator (simDust) and conduct a number of simulations in order to study the effect of obstacles on the performance of some representative (in terms of their logic) data propagation protocols for wireless sensor networks. Our findings confirm that obstacle presence has a significant impact on protocol performance, and also that different obstacle shapes and sizes may affect each protocol in different ways. This provides an insight into how a routing protocol will perform in the presence of obstacles and highlights possible protocol shortcomings. Moreover, our results show that the effect of obstacles is not directly related to the density of a sensor network, and cannot be emulated only by changing the network density.
Abstract: Ever-increasing 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 techno-economically 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: 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 non-homogeneous 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 peer-to-peer 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: 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 real-time 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 low-end and high-end 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: We present three new coordination mechanisms for schedul-
ing n sel¯sh jobs on m unrelated machines. A coordination
mechanism aims to mitigate the impact of sel¯shness of jobs
on the e±ciency of schedules by de¯ning a local schedul-
ing policy on each machine. The scheduling policies induce
a game among the jobs and each job prefers to be sched-
uled on a machine so that its completion time is minimum
given the assignments of the other jobs. We consider the
maximum completion time among all jobs as the measure
of the e±ciency of schedules. The approximation ratio of
a coordination mechanism quanti¯es the e±ciency of pure
Nash equilibria (price of anarchy) of the induced game. Our
mechanisms are deterministic, local, and preemptive in the
sense that the scheduling policy does not necessarily process
the jobs in an uninterrupted way and may introduce some
idle time. Our ¯rst coordination mechanism has approxima-
tion ratio O(logm) and always guarantees that the induced
game has pure Nash equilibria to which the system con-
verges in at most n rounds. This result improves a recent
bound of O(log2 m) due to Azar, Jain, and Mirrokni and,
similarly to their mechanism, our mechanism uses a global
ordering of the jobs according to their distinct IDs. Next
we study the intriguing scenario where jobs are anonymous,
i.e., they have no IDs. In this case, coordination mechanisms
can only distinguish between jobs that have diffeerent load
characteristics. Our second mechanism handles anonymous
jobs and has approximation ratio O
¡ logm
log logm
¢
although the
game induced is not a potential game and, hence, the exis-
tence of pure Nash equilibria is not guaranteed by potential
function arguments. However, it provides evidence that the
known lower bounds for non-preemptive coordination mech-
anisms could be beaten using preemptive scheduling poli-
cies. Our third coordination mechanism also handles anony-
mous jobs and has a nice \cost-revealing" potential func-
tion. Besides in proving the existence of equilibria, we use
this potential function in order to upper-bound the price of stability of the induced game by O(logm), the price of an-
archy by O(log2 m), and the convergence time to O(log2 m)-
approximate assignments by a polynomial number of best-
response moves. Our third coordination mechanism is the
¯rst that handles anonymous jobs and simultaneously guar-
antees that the induced game is a potential game and has
bounded price of anarchy.
Abstract: Through recent technology advances in the eld of wireless energy transmission, Wireless Rechargeable Sensor Networks
(WRSN) have emerged. In this new paradigm for
WSNs a mobile entity called Mobile Charger (MC) traverses
the network and replenishes the dissipated energy of sensors.
In this work we rst provide a formal de nition of the charging
dispatch decision problem and prove its computational
hardness. We then investigate how to optimize the tradeo
s of several critical aspects of the charging process such
as a) the trajectory of the charger, b) the di erent charging
policies and c) the impact of the ratio of the energy
the MC may deliver to the sensors over the total available
energy in the network. In the light of these optimizations,
we then study the impact of the charging process to the
network lifetime for three characteristic underlying routing
protocols; a greedy protocol, a clustering protocol and an
energy balancing protocol. Finally, we propose a Mobile
Charging Protocol that locally adapts the circular trajectory
of the MC to the energy dissipation rate of each sub-region
of the network. We compare this protocol against several
MC trajectories for all three routing families by a detailed
experimental evaluation. The derived ndings demonstrate
signi cant performance gains, both with respect to the no
charger case as well as the di erent charging alternatives; in
particular, the performance improvements include the network
lifetime, as well as connectivity, coverage and energy
balance properties.
Abstract: We call radiation at a point of a wireless network the total amount of electromagnetic quantity (energy or power density) the point is exposed to. The impact of radiation can be high and we believe it is worth studying and control; towards radiation aware wireless networking we take (for the first time in the study of this aspect) a distributed computing, algorithmic approach. We exemplify this line of research by focusing on sensor networks, studying the minimum radiation path problem of finding the lowest radiation trajectory of a person moving from a source to a destination point in the network region. For this problem, we sketch the main ideas behind a linear program that can provide a tight approximation of the optimal solution, and then we discuss three heuristics that can lead to low radiation paths. We also plan to investigate the impact of diverse node mobility to the heuristics' performance.
Abstract: Urban ecosystems are becoming one of the most potentially attractive scenarios for innovating new services and technologies. In parallel, city managers, urban utilities and other stakeholders are fostering the intensive use of advanced technologies aiming at improving present city performance and its sustainability. The deployment of such technology entails the generation of massive amounts of information which in many cases might become useful for other services and applications. Hence, aiming at taking advantage of such massive amounts of information and deployed technology as well as breaking the potential digital barrier that can be raised, some easy-to-use tools have to be made available to the urban stakeholders. These tools integrated in a platform, operated directly or indirectly by the city, provides a singular opportunity for exploiting the concept of connected city whilst fostering innovation in all city dimensions and making the co-creation concept a reality and eventually impacting on government policies.
Abstract: In this paper, we demonstrate the significant impact of (a) the mobility rate and (b) the user density on the performance of routing protocols in ad-hoc mobile networks. In particular, we study the effect of these parameters on two different approaches for designing routing protocols: (a) the route creation and maintenance approach and (b) the support approach that forces few hosts to move, acting as helpers for message delivery. We study one representative protocol for each approach, i.e. AODV for the first approach and RUNNERS for the second. We have implemented the two protocols and performed a large scale and detailed simulation study of their performance. The main findings are: the AODV protocol behaves well in networks of high user density and low mobility rate, while its performance drops for sparse networks of highly mobile users. On the other hand, the RUNNERS protocol seems to tolerate well (and in fact benefit from) high mobility rates and low densities.
Abstract: Core optical networks using reconfigurable optical
switches and tunable lasers appear to be on the road towards
widespread deployment and could evolve to all-optical mesh
networks in the coming future. Considering the impact of physical
layer impairments in the planning and operation of all-optical
(and translucent) networks is the main focus of the DICONET
project. The impairment aware network planning and operation
tool (NPOT) is the main outcome of DICONET project, which
is explained in detail in this paper. The key building blocks of
the NPOT, consisting of network description repositories, the
physical layer performance evaluator, the impairment aware
routing and wavelength assignment engines, the component
placement modules, failure handling and the integration of
NPOT in the control plane are the main contributions of this
work. Besides, the experimental result of DICONET proposal for
centralized and distributed control plane integration schemes and
the performance of the failure handling in terms of restoration
time is presented in this work.
Abstract: We investigate the impact of multiple, mobile sinks on
efficient data collection in wireless sensor networks. To
improve performance, our protocol design focuses on minimizing
overlaps of sink trajectories and balancing the service load
among the sinks. To cope with high network dynamics, placement
irregularities and limited network knowledge we propose three different
protocols: a) a centralized one, that explicitly equalizes spatial coverage;
this protocol assumes strong modeling assumptions, and also serves as a kind
of performance lower bound in uniform networks of low dynamics b)
a distributed protocol based on mutual avoidance of sinks c) a clustering
protocol that distributively groups service areas towards balancing the load per sink.
Our simulation findings demonstrate significant gains in latency, while keeping the success
rate and the energy dissipation at very satisfactory levels even under
high network dynamics and deployment heterogeneity.
Abstract: A fundamental approach in finding efficiently best routes or optimal itineraries in traffic information
systems is to reduce the search space (part of graph visited) of the most commonly used
shortest path routine (Dijkstra¢s algorithm) on a suitably defined graph. We investigate reduction
of the search space while simultaneously retaining data structures, created during a preprocessing
phase, of size linear (i.e., optimal) to the size of the graph. We show that the search space of
Dijkstra¢s algorithm can be significantly reduced by extracting geometric information from a given
layout of the graph and by encapsulating precomputed shortest-path information in resulted geometric
objects (containers). We present an extensive experimental study comparing the impact of
different types of geometric containers using test data from real-world traffic networks. We also
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 geometric containers have to be updated and show that
our new methods are two to three times faster than recomputing everything from scratch. Finally,
in an appendix, we discuss the software framework that we developed to realize the implementations
of all of our variants of Dijkstra¢s algorithm. Such a framework is not trivial to achieve as our
goal was to maintain a common code base that is, at the same time, small, efficient, and flexible,
as we wanted to enhance and combine several variants in any possible way.
Abstract: In load balancing games, there is a set of available servers and
a set of clients; each client wishes to run her job on some server. Clients
are sel¯sh and each of them selects a server that, given an assignment
of the other clients to servers, minimizes the latency she experiences
with no regard to the global optimum. In order to mitigate the e®ect of
sel¯shness on the e±ciency, we assign taxes to the servers. In this way,
we obtain a new game where each client aims to minimize the sum of
the latency she experiences and the tax she pays. Our objective is to
¯nd taxes so that the worst equilibrium of the new game is as e±cient
as possible. We present new results concerning the impact of taxes on
the e±ciency of equilibria, with respect to the total latency of all clients
and the maximum latency (makespan).
Abstract: In this work, we study the impact of the dynamic changing of the network link capacities on the stability properties of packet-switched networks. Especially, we consider the Adversarial, Quasi-Static 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 (Longest-in-System) 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 (Shortest-in-System), NTS (Nearest-to-Source), and FTG (Furthest-to-Go) 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 propose an obstacle model to be used while simulating wireless sensor networks. To the best of our knowledge, this is the first time such an integrated and systematic obstacle model appears. We define several types of obstacles that can be found inside the deployment area of a wireless sensor network and provide a categorization of these obstacles, based on their nature (physical and communication obstacles), their shape, as well as
their nature to change over time. In light of this obstacle model we conduct extensive simulations in order to study the effects of obstacles on the performance of representative data propagation protocols for wireless sensor networks. Our findings
show that obstacle presence has a significant impact on protocol performance. Also, we demonstrate the effect of each obstacle type on different protocols, thus providing the network designer with advice on which protocol is best to use.
Abstract: In this paper we demonstrate the significant impact of (a) the mobility rate and (b) the user density on the performance of routing protocols in ad-hoc mobile networks. In particular, we study the effect of these parameters on two different approaches for designing routing protocols: (a) the route creation and maintenance approach and (b) the "support" approach, that forces few hosts to move acting as "helpers" for message delivery. We study one representative protocol for each approach, i.e., AODV for the first approach and RUNNERS for the second. We have implemented the two protocols and performed a large scale and detailed simulation study of their performance. For the first time, we study AODV (and RUNNERS) in the 3D case. The main findings are: the AODV protocol behaves well in networks of high user density and low mobility rate, while its performance drops for sparse networks of highly mobile users. On the other hand, the RUNNERS protocol seems to tolerate well (and in fact benefit from) high mobility rates and low densities. Thus, we are able to partially answer an important conjecture of [Chatzigiannakis, I et al. 2003].
Abstract: In sponsored search auctions, advertisers compete for a number
of available advertisement slots of different quality. The
auctioneer decides the allocation of advertisers to slots using
bids provided by them. Since the advertisers may act
strategically and submit their bids in order to maximize their
individual objectives, such an auction naturally defines a
strategic game among the advertisers. In order to quantify
the efficiency of outcomes in generalized second price auctions,
we study the corresponding games and present new
bounds on their price of anarchy, improving the recent results
of Paes Leme and Tardos [16] and Lucier and Paes
Leme [13]. For the full information setting, we prove a surprisingly
low upper bound of 1.282 on the price of anarchy
over pure Nash equilibria. Given the existing lower bounds,
this bound denotes that the number of advertisers has almost
no impact on the price of anarchy. The proof exploits
the equilibrium conditions developed in [16] and follows by
a detailed reasoning about the structure of equilibria and a
novel relation of the price of anarchy to the objective value
of a compact mathematical program. For more general equilibrium
classes (i.e., mixed Nash, correlated, and coarse correlated
equilibria), we present an upper bound of 2.310 on
the price of anarchy. We also consider the setting where
advertisers have incomplete information about their competitors
and prove a price of anarchy upper bound of 3.037
over Bayes-Nash equilibria. In order to obtain the last two
bounds, we adapt techniques of Lucier and Paes Leme [13]
and significantly extend them with new arguments
Abstract: In future transparent optical networks, it is
important to consider the impact of physical impairments in the
routing and wavelengths assignment process, to achieve efficient
connection provisioning. In this paper, we use classical multi-
objective optimization (MOO) strategies and particularly genetic
algorithms to jointly solve the impairment aware RWA (IA-
RWA) problem. Fiber impairments are indirectly considered
through the insertion of the path length and the number of
common hops in the optimization process. It is shown that
blocking is greatly improved, while the obtained solutions truly
converge towards the Pareto front that constitutes the set of
global optimum solutions. We have evaluated our findings, using
an Q estimator tool, that calculates the signal quality of each path
analytically.
Index Terms RWA, Genetic Algorithm, All-Optical
Networks, Multi Objective Optimization.
Abstract: In this work, we study the impact of dynamically changing
link capacities on the delay bounds of LIS (Longest-In-
System) and SIS (Shortest-In-System) 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] withC > 1, under a (w, \~{n})-
adversary.
Abstract: In this work, we study the impact of dynamically changing link capacities on the delay bounds of LIS (Longest-In-System) and SIS (Shortest-In-System) 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: With a rapidly aging population, the health-care community will
soon face a severe medical personnel shortage. It is imperative that automated
health monitoring technologies be developed to help meet this
shortage. In this direction, we are developing Ayushman, a health monitoring
infrastructure and testbed. The vision behind its development
is two-fold: first, to develop a wireless sensor-based automated health
monitoring system that can be used in diverse situations, from homebased
care, to disaster situations, without much customization; second,
to provide a testbed for implementing and testing communication protocols
and systems. Ayushman provides a collection of services which
enables it to perform this dual role. It possess a hierarchical cluster
topology which provides a fault-tolerant and reliable system by ensuring
that each tier in the hierarchy is self-contained and can survive on its
own in case of network partition. Ayushman is being implemented using
off-the-shelf and diverse hardware and software components, which
presents many challenges in system integration and operational reliability.
This is an ongoing project at the IMPACT lab at Arizona State
University1, and in this paper, we present our system¢s architecture and
some of our experiences in the development of its initial prototype.
Abstract: This research attempts a first step towards investigating the aspect of radiation awareness in environments with abundant heterogeneous wireless networking. We call radiation at a point of a 3D wireless network the total amount of electromagnetic quantity the point is exposed to, our definition incorporates the effect of topology as well as the time domain, data traffic and environment aspects. Even if the impact of radiation to human health remains largely unexplored and controversial, we believe it is worth trying to understand and control. We first analyze radiation in well known topologies (random and grids), randomness is meant to capture not only node placement but also uncertainty of the wireless propagation model. This initial understanding of how radiation adds (over space and time) can be useful in network design, to reduce health risks. We then focus on the minimum radiation path problem of finding the lowest radiation trajectory of a person moving from a source to a destination point of the network region. We propose three heuristics which provide low radiation paths while keeping path length low, one heuristic gets in fact quite close to the offline solution we compute by a shortest path algorithm. Finally, we investigate the interesting impact on the heuristics' performance of diverse node mobility.
Abstract: This research further investigates the recently introduced
(in [4]) paradigm of radiation awareness in ambient environments with abundant heterogeneous wireless networking
from a distributed computing perspective. We call radiation
at a point of a wireless network the total amount of electromagnetic quantity the point is exposed to; our de nition incorporates the e ect of topology as well as the time domain
and environment aspects. Even if the impact of radiation to
human health remains largely unexplored and controversial,
we believe it is worth trying to understand and control, in
a way that does not decrease much the quality of service
o ered to users of the wireless network.
In particular, we here focus on the fundamental problem
of ecient data propagation in wireless sensor networks, try-
ing to keep latency low while maintaining at low levels the
radiation cumulated by wireless transmissions. We rst propose greedy and oblivious routing heuristics that are radiation aware. We then combine them with temporal back-o
schemes that use local properties of the network (e.g. number of neighbours, distance from sink) in order to spread" radiation in a spatio-temporal way. Our proposed radiation
aware routing heuristics succeed to keep radiation levels low,
while not increasing latency.
Abstract: In this paper we demonstrate the significant impact of the user mobility rates on the performance on two different approaches for designing routing protocols for ad-hoc mobile networks: (a) the route creation and maintenance approach and (b) the "support" approach, that forces few hosts to move acting as
"helpers" for message delivery. We study a set of representative protocols for each approach, i.e.~DSR and ZRP for the first approach and RUNNERS for the second. We have implemented the three protocols and performed a large scale and detailed simulation study of their performance. Our findings are: (i) DSR achieves low message delivery rates but manages to deliver messages very fast; (ii) ZRP behaves well in networks of low mobility rate, while its performance drops for networks of highly mobile users; (iii) RUNNERS seem to tolerate well (and in fact benefit from) high mobility rates.
Based on our investigation, we design and implement two new protocols that result from the synthesis of the investigated routing approaches. We conducted an extensive, comparative simulation study of their performance. The new protocols behave well both in networks of diverse mobility motion rates, and in some cases they even outperform the original ones by achieving lower message delivery delays.
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 study a problem of scheduling client requests to servers. Each client has a particular latency requirement at each server and may choose either to be assigned to some server in order to get serviced provided that her latency requirement is met, or not to participate in the assignment at all. From a global perspective, in order to optimize the performance of such a system, one would aim to maximize the number of clients that participate in the assignment. However, clients may behave selfishly in the sense that, each of them simply aims to participate in an assignment and get serviced by some server where her latency requirement is met with no regard to overall system performance. We model this selfish behavior as a strategic game, show how to compute pure Nash equilibria efficiently, and assess the impact of selfishness on system performance. We also show that the problem of optimizing performance is computationally hard to solve, even in a coordinated way, and present efficient approximation and online algorithms.
Abstract: We study a problem of scheduling client requests to servers.
Each client has a particular latency requirement at each server and may
choose either to be assigned to some server in order to get serviced provided
that her latency requirement is met or not to participate in the
assignment at all. From a global perspective, in order to optimize the
performance of such a system, one would aim to maximize the number
of clients that participate in the assignment. However, clients may behave
selfishly in the sense that each of them simply aims to participate
in an assignment and get serviced by some server where her latency requirement
is met with no regard to the overall system performance. We
model this selfish behavior as a strategic game, show how to compute
equilibria efficiently, and assess the impact of selfishness on system performance.
We also show that the problem of optimizing performance is
computationally hard to solve, even in a coordinated way, and present
efficient approximation and online algorithms.
Abstract: We investigate the impact of different mobility rates on the
performance of routing protocols in ad-hoc mobile networks. Based
on our investigation, we design a new protocol that results from
the synthesis of the well known protocols: ZRP and RUNNERS. We have implemented the new protocol as well as
the original two protocols and conducted an extensive, comparative
simulation study of their performance. The new protocol behaves
well both in networks of diverse mobility motion rates, and in
some cases even outperforms the original ones by achieving lower
message delivery delays.
Abstract: We study congestion games where players aim to access a set of resources. Each player has a set of possible strategies and each resource has a function associating the latency it incurs to the players using it. Players are non–cooperative and each wishes to follow strategies that minimize her own latency with no regard to the global optimum. Previous work has studied the impact of this selfish behavior to system performance. In this paper, we study the question of how much the performance can be improved if players are forced to pay taxes for using resources. Our objective is to extend the original game so that selfish behavior does not deteriorate performance. We consider atomic congestion games with linear latency functions and present both negative and positive results. Our negative results show that optimal system performance cannot be achieved even in very simple games. On the positive side, we show that there are ways to assign taxes that can improve the performance of linear congestion games by forcing players to follow strategies where the total latency suffered is within a factor of 2 of the minimum possible; this result is shown to be tight. Furthermore, even in cases where in the absence of taxes the system behavior may be very poor, we show that the total disutility of players (latency plus taxes) is not much larger than the optimal total latency. Besides existential results, we show how to compute taxes in time polynomial in the size of the game by solving convex quadratic programs. Similar questions have been extensively studied in the model of non-atomic congestion games. To the best of our knowledge, this is the first study of the efficiency of taxes in atomic congestion games.
Abstract: We study the impact of fairness on the e±ciency of allo-
cations. We consider three di®erent notions of fairness, namely propor-
tionality, envy-freeness, and equitability for allocations of divisible and
indivisible goods and chores. We present a series of results on the price of
fairness under the three di®erent notions that quantify the e±ciency loss
in fair allocations compared to optimal ones. Most of our bounds are ei-
ther exact or tight within constant factors. Our study is of an optimistic
nature and aims to identify the potential of fairness in allocations.
Abstract: A packet-switching network is stable if the number of packets in the network remains bounded at all times. A very natural question that arises in the context of stability properties of such networks is how network structure precisely affects these properties. In this work we embark on a systematic study of this question in the context of Adversarial Queueing Theory, which assumes that packets are adversarially injected into the network. We consider size, diameter, maximum vertex degree, minimum number of disjoint paths that cover all edges of the network and network subgraphs as crucial structural parameters of the network, and we present a comprehensive collection of structural results, in the form of stability and instability bounds on injection rate of the adversary for various greedy protocols: —Increasing the size of a network may result in dropping its instability bound. This is shown through a novel, yet simple and natural, combinatorial construction of a size-parameterized network on which certain compositions of greedy protocols are running. The convergence of the drop to 0.5 is found to be fast with and proportional to the increase in size. —Maintaining the size of a network small may already suffice to drop its instability bound to a substantially low value. This is shown through a construction of a FIFO network with size 22, which becomes unstable at rate 0.704. This represents the current state-of-the-art trade-off between network size and instability bound. —The diameter, maximum vertex degree and minimum number of edge-disjoint paths that cover a network may be used as control parameters for the stability bound of the network. This is shown through an improved analysis of the stability bound of any arbitrary FIFO network, which takes these parameters into account. —How much can network subgraphs that are forbidden for stability affect the instability bound? Through improved combinatorial constructions of networks and executions, we improve the state-of-the-art instability bound induced by certain known forbidden subgraphs on networks running a certain greedy protocol. —Our results shed more light and contribute significantly to a finer understanding of the impact of structural parameters on stability and instability properties of networks.
Abstract: In this work, we study the impact of the dynamic changing of the network link capacities on the stability properties of packet-switched networks. Especially, we consider the Adversarial, Quasi-Static 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 (Longest-in-System) 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 (Shortest-in-System), NTS (Nearest-to-Source), and FTG (Furthest-to-Go) 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: We study the load balancing problem in the context of a set of clients each wishing to run a job on a server selected among a subset of permissible servers for the particular client. We consider two different scenarios. In selfish load balancing, each client is selfish in the sense that it selects to run its job to the server among its permissible servers having the smallest latency given the assignments of the jobs of other clients to servers. In online load balancing, clients appear online and, when a client appears, it has to make an irrevocable decision and assign its job to one of its permissible servers. Here, we assume that the clients aim to optimize some global criterion but in an online fashion. A natural local optimization criterion that can be used by each client when making its decision is to assign its job to that server that gives the minimum increase of the global objective. This gives rise to greedy online solutions. The aim of this paper is to determine how much the quality of load balancing is affected by selfishness and greediness.
We characterize almost completely the impact of selfishness and greediness in load balancing by presenting new and improved, tight or almost tight bounds on the price of anarchy and price of stability of selfish load balancing as well as on the competitiveness of the greedy algorithm for online load balancing when the objective is to minimize the total latency of all clients on servers with linear latency functions.
Abstract: We study the load balancing problem in the context of a set of clients each
wishing to run a job on a server selected among a subset of permissible servers for
the particular client. We consider two different scenarios. In selfish load balancing,
each client is selfish in the sense that it chooses, among its permissible servers, to
run its job on the server having the smallest latency given the assignments of the
jobs of other clients to servers. In online load balancing, clients appear online and,
when a client appears, it has to make an irrevocable decision and assign its job to
one of its permissible servers. Here, we assume that the clients aim to optimize some
global criterion but in an online fashion. A natural local optimization criterion that
can be used by each client when making its decision is to assign its job to that server that gives the minimum increase of the global objective. This gives rise to greedy
online solutions. The aim of this paper is to determine how much the quality of load
balancing is affected by selfishness and greediness.
We characterize almost completely the impact of selfishness and greediness in
load balancing by presenting new and improved, tight or almost tight bounds on the
price of anarchy of selfish load balancing as well as on the competitiveness of the
greedy algorithm for online load balancing when the objective is to minimize the
total latency of all clients on servers with linear latency functions. In addition, we
prove a tight upper bound on the price of stability of linear congestion games.
Abstract: In this paper, the impact of burstification delay on the TCP
traffic statistics is presented as well as a new assembly scheme that uses
flow window size as the threshold criterion. It is shown that short assembly
times are ideally suitable for sources with small congestion windows,
allowing for a speed up in their transmission. In addition, large assembly
times do not yield any throughput gain, despite the large number of
segments per burst transmitted, but result in a low throughput variation, and
thus a higher notion of fairness among the individual flows. To this end, in
this paper, we propose a new burst assembly scheme that dynamically
assigns flows to different assembly queues with different assembly timers,
based on their instant window size. Results show that the proposed scheme
with different timers provides a higher average throughput together with a
smaller variance which is a good compromise for bandwidth dimensioning.
Abstract: Numerous research efforts have produced a large number of algorithms and mechanisms for web proxy caches. In order to build powerful web proxies and understand their performance, one must be able to appreciate the impact and significance of earlier contributions and how they can be integrated. To do this we employ a cache replacement algorithm, 'CSP', which integrates key knowledge from previous work. CSP utilizes the communication Cost to fetch web objects, the objects' Sizes, their Popularities, an auxiliary cache and a cache admission control algorithm. We study the impact of these components with respect to hit ratio, latency, and bandwidth requirements.
Numerous research efforts have produced a large number of algorithms and mechanisms for web proxy caches. In order to build powerful web proxies and understand their performance, one must be able to appreciate the impact and significance of earlier contributions and how they can be integrated To do this we employ a cache replacement algorithm, 'CSP, which integrates key knowledge from previous work. CSP utilizes the communication Cost to fetch web objects, the objects' Sizes, their Popularifies, an auxiliary cache and a cache admission control algorithm. We study the impact of these components with respect to hit ratio, latency, and bandwidth requirements. Our results show that there are clear performance gains when utilizing the communication cost, the popularity of objects, and the auxiliary cache. In contrast, the size of objects and the admission controller have a negligible performance impact. Our major conclusions going against those in related work are that (i) LRU is preferable to CSP for important parameter values, (ii) accounting for the objects' sizes does not improve latency and/or bandwidth requirements, and (iii) the collaboration of nearby proxies is not very beneficial. Based on these results, we chart the problem solution space, identifying which algorithm is preferable and under which conditions. Finally, we develop a dynamic replacement algorithm that continuously utilizes the best algorithm as the problem-parameter values (e.g., the access distributions) change with time.
