Abstract: We here present the Forward Planning Situated Protocol (FPSP), for scalable, energy efficient and fault tolerant data propagation in situated wireless sensor networks. To deal with the increased complexity of such deeply networked sensor systems, instead of emphasizing on a particular aspect of the services provided, i.e. either for low-energy periodic, or low-latency event-driven, or high-success query-based sensing, FPSP uses two novel mechanisms that allow the network operator to adjust the performance of the protocol in terms of energy, latency and success rate on a per-task basis. We emphasize on distributedness, direct or indirect interactions among relatively simple agents, flexibility and robustness.
The protocol operates by employing a series of plan & forward phases through which devices self-organize into forwarding groups that propagate data over discovered paths. FPSP performs a limited number of long range, high power data transmissions to collect information regarding the neighboring devices. The acquired information, allows to plan a (parameterizable long by {\"e}) sequence of short range, low power transmissions between nearby particles, based on certain optimization criteria. All particles that decide to respond (based on local criteria) to these long range transmissions enter the forwarding phase during which information is propagated via the acquired plan. Clearly, the duration of the forwarding phases is characterized by the parameter {\"e}, the transmission medium and the processing speed of the devices. In fact the parameter {\"e} provides a mechanism to adjust the protocol performance in terms of the latency--energy trade-off. By reducing {\"e} the latency is reduced at the cost of spending extra energy, while by increasing {\"e}, the energy dissipation is reduced but the latency is increased.
To control the success rate--energy trade-off, particles react locally on environment and context changes by using a set of rules that are based on response thresholds that relate individual-level plasticity with network-level resiliency, motivated by the nature-inspired method for dividing labor, a metaphor of social insect behavior for solving problems [1]. Each particle has an individual response threshold {\`E} that is related to the "local" density (as observed by the particle, [2]); particles engage in propagation of events when the level of the task-associated stimuli exceeds their thresholds. Let s be the intensity of a stimulus associated with a particular sensing task, set by the human authorities. We adopt the response function T_{{\`e}}(s) = s^{n}over s^{n} + {\`e}^{n}, the probability of performing the task as a function of s, where n > 1 determines the steepness of the threshold. Thus, when {\`e} is small (i.e. the network is sparse) then the response probability increases; when s increases (i.e. for critical sensing tasks) the response probability increases as well.
This role-based approach where a selective number of devices do the high cost planning and the rest of the network operates in a low cost state leads to systems that have increased energy efficiency and high fault-tolerance since these long range planning phases allow to bypass obstacles (where no sensors are available) or faulty sensors (that have been disabled due to power failure or other natural events).

Abstract: We describe the design and implementation
of a secure and robust architectural data management
model suitable for cultural environments. Usage and exploitation
of the World Wide Web is a critical requirement
for a series of administrative tasks such as collecting, managing
and distributing valuable cultural and artistic information.
This requirement introduces a great number of
Internet threats for cultural organizations that may cause
huge data and/or financial losses, harm their reputation
and public acceptance as well as people’s trust on them.
Our model addresses a list of fundamental operational
and security requirements. It utilizes a number of cryptographic
primitives and techniques that provide data safety
and secure user interaction on especially demanding online
collaboration environments. We provide a reference
implementation of our architectural model and discuss
the technical issues. It is designed as a standalone solution
but it can be flexibly adapted in broader management
infrastructures.

Abstract: Usage and exploitation of the Internet is a critical requirement for managing and distributing valuable digital assets. This requirement introduces a great number of threats for commercial (or not) organizations that may cause huge data and financial losses, harm their reputation as well as people's trust on them. In this paper we present the research challenges for secure digital asset management over the web by proposing a model that provides data safety and secure user interaction on especially demanding on-line collaboration environments.

Abstract: We discuss some new algorithmic and complexity issues in
coalitional and dynamic/evolutionary games, related to the understand-
ing of modern sel¯sh and Complex networks.
In particular: (a) We examine the achievement of equilibria via natural
distributed and greedy approaches in networks. (b) We present a model
of a coalitional game in order to capture the anarchy cost and complexity
of constructing equilibria in such situations. (c) We propose a stochastic
approach to some kinds of local interactions in networks, that can be
viewed also as extensions of the classical evolutionary game theoretic
setting.

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 ICT-2008-215270 (FRONTS). Also supported by Research Training Group GK-693 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 k-colouring 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: In this work, we overview some results concerning communication combinatorial properties in random intersection graphs and uniform random intersection 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 present and discuss results concerning the existence of large independent sets of vertices whp in random instances of each of these models. As the main contribution of our paper, we introduce a new, general model, which we denote G(V, χ, f). In this model, V is a set of vertices and χ is a set of m vectors in ℝm. Furthermore, f is a probability distribution over the powerset 2χ of subsets of χ. Every vertex selects a random subset of vectors according to the probability f and two vertices are connected according to a general intersection rule depending on their assigned set of vectors. Apparently, this new general model seems to be able to simulate other known random graph models, by carefully describing its intersection rule.

Abstract: We survey here some recent computational models for networks of tiny artifacts. In particular, we focus on networks consisting of artifacts with sensing capabilities. We first imagine the artifacts moving passively, that is, being mobile but unable to control their own movement. This leads us to the population protocol model of Angluin et al. (2004) [16]. We survey this model and some of its recent enhancements. In particular, we also present the mediated population protocol model in which the interaction links are capable of storing states and the passively mobile machines model in which the finite state nature of the agents is relaxed and the agents become multitape Turing machines that use a restricted space. We next survey the sensor field model, a general model capturing some identifying characteristics of many sensor network¢s settings. A sensor field is composed of kinds of devices that can communicate one to the other and also to the environment through input/output data streams. We, finally, present simulation results between sensor fields and population protocols and analyze the capability of their variants to decide graph properties

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: 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: Evolutionary Game Theory is the study of strategic interactions
among large populations of agents who base their decisions on simple,
myopic rules. A major goal of the theory is to determine broad classes
of decision procedures which both provide plausible descriptions of selfish
behaviour and include appealing forms of aggregate behaviour. For example,
properties such as the correlation between strategies¢ growth rates
and payoffs, the connection between stationary states and the well-known
game theoretic notion of Nash equilibria, as well as global guarantees of
convergence to equilibrium, are widely studied in the literature.
Our paper can be seen as a quick introduction to Evolutionary Game
Theory, together with a new research result and a discussion of many
algorithmic and complexity open problems in the area. In particular, we
discuss some algorithmic and complexity aspects of the theory, which
we prefer to view more as Game Theoretic Aspects of Evolution rather
than as Evolutionary Game Theory, since the term “evolution” actually
refers to strategic adaptation of individuals¢ behaviour through a
dynamic process and not the traditional evolution of populations. We
consider this dynamic process as a self-organization procedure which,
under certain conditions, leads to some kind of stability and assures robustness
against invasion. In particular, we concentrate on the notion of
the Evolutionary Stable Strategies (ESS). We demonstrate their qualitative
difference from Nash Equilibria by showing that symmetric 2-person
games with random payoffs have on average exponentially less ESS than
Nash Equilibria. We conclude this article with some interesting areas of
future research concerning the synergy of Evolutionary Game Theory
and Algorithms.

Abstract: Evolutionary Game Theory is the study of strategic interactions among large populations of agents who base their decisions on simple, myopic rules. A major goal of the theory is to determine broad classes of decision procedures which both provide plausible descriptions of selfish behaviour and include appealing forms of aggregate behaviour. For example, properties such as the correlation between strategies' growth rates and payoffs, the connection between stationary states and Nash equilibria and global guarantees of convergence to equilibrium, are widely studied in the literature. In this paper we discuss some computational aspects of the theory, which we prefer to view more as Game Theoretic Aspects of Evolution than Evolutionary Game Theory, since the term "evolution" actually refers to strategic adaptation of individuals ' behaviour through a dynamic process and not the traditional evolution of populations. We consider this dynamic process as a self-organization procedure, which under certain conditions leads to some kind of stability and assures robustness against invasion.

Abstract: The technological as well as software advances in
microelectronics and embedded component design have led to the
development of low cost, small-sized devices capable of forming
wireless, ad-hoc 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: A new social form of play taking place in public spaces, such as city parks, squares and streets that can scale up to involve large number of participants and engage players located simultaneously in dispersed areas is discussed here. This paper presents a platform that allows for the creation of interactive installations in public spaces. The FinN platform provides functionality for detecting and localizing people, by requiring players to carry identifying devices that offer many possibilities for gesture interaction (i.e., gestures such as shaking, facilitated by the sensor-bouquet of the devices). One of the deployed example installations, where visitors can interact with words formations, is presented here as a case study.

Abstract: We extend here the Population Protocol model of Angluin et al. [2004,2006] in order to model more powerful networks of resource-limited agents that are possibly mobile. The main feature of our extended model, called the Mediated Population Protocol (MPP) model, is to allow edges of the communication graph to have states that belong to a constant size set. We then allow the protocol rules for pairwise interactions to modify the corresponding edge state. Protocol specifications preserve both uniformity and anonymity. We first focus on the computational power of the MPP model on complete communication graphs and initially identical edges. We provide the following exact characterization for the class MPS of stably computable predicates: A predicate is in MPS iff it is symmetric and is in NSPACE(n^2)$. We finally ignore the input to the agents and study MPP's ability to compute graph properties.

Abstract: We extend here the Population Protocol model of Angluin et al. [2004] in order to model more powerful networks of very small resource-limited artefacts (agents) that are possibly mobile. Communication can happen only between pairs of artefacts. A communication graph (or digraph) denotes the permissible pairwise interactions. The main feature of our extended model is to allow edges of the communication graph, G, to have states that belong to a constant size set. We also allow edges to have 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. Thus, our protocol specifications are still independent of the population size and do not use agent ids, i.e. they preserve scalability, uniformity and anonymity. Our 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, by presenting a mediated protocol that stably computes the product of two positive integers, when G is the complete graph. This is not a semilinear predicate. To show this fact, we state and prove a general Theorem about the Composition of two stably computing mediated population protocols. We also show that all predicates stably computable in our model are (non-uniformly) in the class NSPACE(m), where m is the number of edges of the communication graph. We also define Randomized MPP and show that, any Peano predicate accepted by a MPP, can be verified in deterministic Polynomial Time.

Abstract: In this work, we explore context-aware application scenarios that become possible utilizing semantically-rich information derived from real-world mobility and presence traces. Traces produced by people carrying personal mobile devices, capturing social and contextual interactions, serve as enables for Future Internet applications. We discuss the fundamental concepts, technical issues and related research challenges. We propose a reference architecture for setting up a system that collects such traces in a Smart City environment. We present the algorithms used to process the traces and infer interactions and interests for the observed populations. We conduct two 3-day trial deployments: one in an office environment and the other in the context of a Smart Conference application. We discuss our findings regarding the system's capability to track interactions and the overall efficacy of the application.

Abstract: We propose a new theoretical model for passively mobile Wireless Sensor Networks, called PM, standing for Passively mobile Machines. The main modification w.r.t. the Population Protocol model [Angluin et al. 2006] is that agents now, instead of being automata, are Turing Machines. We provide general definitions for unbounded memories, but we are mainly interested in computations upper-bounded by plausible space limitations. However, we prove that our results hold for more general cases. We focus on \emph{complete interaction graphs} and define the complexity classes PMSPACE(f(n)) parametrically, consisting of all predicates that are stably computable by some PM protocol that uses O(f(n)) memory in each agent. We provide a protocol that generates unique identifiers from scratch only by using O(log n) memory, and use it to provide an exact characterization of the classes PMSPACE(f(n)) when f(n) = Ω(log n): they are precisely the classes of all symmetric predicates in NSPACE(nf(n)). As a consequence, we obtain a space hierarchy of the PM model when the memory bounds are Ω(log n). We next explore the computability of the PM model when the protocols use o(loglog n) space per machine and prove that SEM = PMSPACE(f(n)) when f(n) = o(loglog n), where SEM denotes the class of the semilinear predicates. Finally, we establish that the minimal space requirement for the computation of non-semilinear predicates is O(log log n).

Abstract: We propose a new theoretical model for passively mobile Wireless Sensor Networks, called PM, standing for Passively mobile Machines. The main modification w.r.t. the Population Protocol model [Angluin et al. 2006] is that the agents now, instead of being automata, are Turing Machines. We provide general definitions for unbounded memories, but we are mainly interested in computations upper-bounded by plausible space limitations. However, we prove that our results hold for more general cases. We focus on complete interaction graphs and define the complexity classes PMSPACE(f(n)) parametrically, consisting of all predicates that are stably computable by some PM protocol that uses O(f(n)) memory in each agent. We provide a protocol that generates unique identifiers from scratch only by using O(log n) memory, and use it to provide an exact characterization of the classes PMSPACE(f(n)) when f(n)=Omega(log n): they are precisely the classes of all symmetric predicates in NSPACE(nf(n)). As a consequence, we obtain a space hierarchy of the PM model when the memory bounds are Omega(log n). Finally, we establish that the minimal space requirement for the computation of non-semilinear predicates is O(log log n).

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 (non-uniformly) 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: A collection of pervasive street games is presented in this paper, that constitute a new social form of play taking place in public spaces, such as city parks, public spaces and streets. The main characteristic of these games is the ability to scale to a large number of players (in some cases involving more than 40 players) and can engage players located simultaneously in dispersed areas. Players interact with each other using a wide range of hardware devices that are either generic (such as smart phones) or specific (such as wireless sensor devices). We discuss a set of fundamental issues related to game design emphasizing on the one hand the interaction of the players with the ubiquitous computing environment and on the other hand the embedding of the game rules within the environment. The games are developed using open source technologies and evaluated in a series of events such as the Athens Plaython 2012 festival. The feedback received from the players indicates that this new form of gaming is indeed very promising.

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 finite-state 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 finite-state 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 non-zero 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: In this paper we address the problem of capturing and pro-
cessing certain spatiotemporal, social characteristics of hu-
man interactions with the use of Wireless Sensor Networks.
Using TelosB motes, we basically monitor the binary prox-
imity within a group of people. The collected data give an
insight of how people interact with each other (how often,
for how much time, in which room) and provide a novel tool
(which can be further enhanced) to study (quantitatively, in
an automated manner) human social networks.

Abstract: In this paper we address the problem of capturing and pro-
cessing certain spatiotemporal, social characteristics of hu-
man interactions with the use of Wireless Sensor Networks.
Using TelosB motes, we basically monitor the binary prox-
imity within a group of people. The collected data give an
insight of how people interact with each other (how often,
for how much time, in which room) and provide a novel tool
(which can be further enhanced) to study (quantitatively, in
an automated manner) human social 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 well-mixed 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{self-replication}. 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 well-mixed 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 self-organized with high probability into arbitrarily complex shapes while still detecting termination of the construction}.

Abstract: We explore the capability of a network of extremely limited
computational entities to decide properties about any of its subnetworks.
We consider that the underlying network of the interacting
entities (devices, agents, processes etc.) is modeled by a complete in-
teraction graph and we devise simple graph protocols that can decide
properties of some input subgraph provided by some preprocessing on
the network. The agents are modeled as nite-state automata and run
the same global graph protocol. Each protocol is a xed size grammar,
that is, its description is independent of the size (number of agents) of
the network. This size is not known by the agents. We propose a simple
model, the Mediated Graph Protocol (MGP) model, similar to the Population
Protocol model of Angluin et al., in which each network link is
characterized by a state taken from a nite set. This state can be used
and updated during each interaction between the corresponding agents.
We provide some interesting properties of the MGP model among which
is the ability to decide properties on stabilizing (initially changing for a
nite number of steps) input graphs and we show that the MGP model
has the ability to decide properties of disconnected input graphs. We
show that the computational power within the connected components is
fairly restricted. Finally, we give an exact characterization of the class
GMGP, of graph languages decidable by the MGP model: it is equal
to the class of graph languages decidable by a nondeterministic Turing
Machine of linear space that receives its input graph by its adjacency
matrix representation.

Abstract: We explore the capability of a network of extremely limited computational entities to decide properties about itself or any of its subnetworks. We consider that the underlying network of the interacting entities (devices, agents, processes etc.) is modeled by an interaction graph that reflects the network’s connectivity. We examine the following two cases: First, we consider the case where the input graph is the whole interaction graph and second where it is some subgraph of the interaction graph given by some preprocessing on the network. In each case, we devise simple graph protocols that can decide properties of the input graph. The computational entities, that are called agents, are modeled as finite-state automata and run the same global graph protocol. Each protocol is a fixed size grammar, that is, its description is independent of the size (number of agents) of the network. This size is not known by the agents. We present two simple models (one for each case), the Graph Decision Mediated Population Protocol (GDMPP) and the Mediated Graph Protocol (MGP) models, similar to the Population Protocol model of Angluin et al., where each network link (edge of the interaction graph) is characterized by a state taken from a finite set. This state can be used and updated during each interaction between the corresponding agents. We provide some example protocols and some interesting properties for the two models concerning the computability of graph languages in various settings (disconnected input graphs, stabilizing input graphs). We show that the computational power within the family of all (at least) weakly-connected input graphs is fairly restricted. Finally, we give an exact characterization of the class of graph languages decidable by the MGP model in the case of complete interaction graphs: it is equal to the class of graph languages decidable by a nondeterministic Turing Machine of linear space that receives its input graph by its adjacency matrix representation.

Abstract: We address several recent developments in non-cooperative as well as
evolutionary game theory, that give a new viewpoint to Complex Systems understanding.
In particular, we discuss notions like the anarchy cost, equilibria formation,
social costs and evolutionary stability. We indicate how such notions help
in understanding Complex Systems behaviour when the system includes selfish,
antagonistic entities of varying degrees of rationality. Our main motivation is the
Internet, perhaps the most complex artifact to date, as well as large-scale systems
such as the high-level P2P systems, where where the interaction is among
humans, programmes and machines and centralized approaches cannot apply.

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 ad-hoc 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 IST-2005-15964 (AEOLUS) and the INTAS Programme under contract with Ref. No 04-77-7173 (Data Flow Systems: Algorithms and Complexity (DFS-AC)).

Abstract: Recent activity in the field of Internet-of-Things experimentation has focused on the federation of discrete testbeds, thus placing less effort in the integration of other related technologies, such as smartphones; also, while it is gradually moving to more application-oriented paths, such as urban settings, it has not dealt in large with applications having social networking features. We argue here that current IoT infrastructure, testbeds and related software technologies should be used in such a context, capturing real-world human mobility and social networking interactions, for use in evaluating and fine-tuning realistic mobility models and designing human-centric applications. We discuss a system for producing traces for a new generation of human-centric applications, utilizing technologies such as Bluetooth and focusing on human interactions. We describe the architecture for this system and the respective implementation details presenting two distinct deployments; one in an office environment and another in an exhibition/conference event (FET'11, The European Future Technologies Conference and Exhibition) with 103 active participants combined, thus covering two popular scenarios for human centric applications. Our system provides online, almost real-time, feedback and statistics and its implementation allows for rapid and robust deployment, utilizing mainstream technologies and components.

Abstract: In this paper we describe a new simulation platform for complex wireless sensor networks that operate a collection of distributed algorithms and network protocols. Simulating such systems is complicated because of the need to coordinate different network layers and debug protocol stacks, often with very different interfaces, options, and fidelities. Our platform (which we call WSNGE) is a flexible and extensible environment that provides a highly scalable simulator with unique characteristics. It focuses on user friendliness, providing every function in both scriptable and visual way, allowing the researcher to define simulations and view results in an easy to use graphical environment. Unlike other solutions, WSNGE does not distinguish between different scenario types, allowing multiple different protocols to run at the same time. It enables rich online interaction with running simulations, allowing parameters, topologies or the whole scenario to be altered at any point in time.