Abstract: We consider algorithmic questions concerning the existence, tractability and quality of Nash equi-
libria, in atomic congestion games among users participating in selsh coalitions.
We introduce a coalitional congestion model among atomic players and demonstrate many in-
teresting similarities with the non-cooperative case. For example, there exists a potentialfunction
proving the existence of Pure Nash Equilibria (PNE) in the unrelated parallel links setting; in
the network setting, the Finite Improvement Property collapses as soon as we depart from linear
delays, but there is an exact potential (and thus PNE) for linear delays; the Price of Anarchy on
identical parallel links demonstrates a quite surprising threshold behavior: it persists on being
asymptotically equal to that in the case of the non-cooperative KP-model, unless the number of
coalitions is sublogarithmic.
We also show crucial dierences, mainly concerning the hardness of algorithmic problems that
are solved eciently in the non{cooperative case. Although we demonstrate convergence to robust
PNE, we also prove the hardness of computing them. On the other hand, we propose a generalized
fully mixed Nash Equilibrium, that can be eciently constructed in most cases. Finally, we
propose a natural improvement policy and prove its convergence in pseudo{polynomial time to
PNE which are robust against (even dynamically forming) coalitions of small size.

Abstract: We study here the effect of concurrent greedy moves of players in atomic congestion games
where n selfish agents (players) wish to select a resource each (out of m resources) so that her selfish delay there is not much. Such games usually admit a global potential that decreases by sequential and selfishly improving moves. However, concurrent moves may not always lead to global convergence. On the other hand, concurrent play is desirable because it might essentially improve the system convergence time to some balanced state. The problem of ?maintaining? global progress while allowing concurrent play is
exactly what is examined and answered here. We examine two orthogonal settings : (i) A game where the players decide their moves without global information, each acting ?freely? by sampling resources randomly and locally deciding to migrate (if the new resource is better) via a random experiment. Here, the resources can have quite arbitrary latency that is load dependent. (ii) An ?organised? setting where the players are prepartitioned into selfish groups (coalitions) and where each coalition does an improving coalitional move.
Here the concurrency is among the members of the coalition. In this second setting, the resources have latency functions that are only linearly dependent on the load, since this is the only case so far where a global potential exists. In both cases (i), (ii) we show that the system converges to an ?approximate? equilibrium very fast (in logarithmic rounds where the logarithm is taken on the maximum value of the global potential). This is interesting, since two quite orthogonal settings lead to the same result. Our work considers concurrent selfish play for arbitrary latencies for the first time. Also, this is the first time where fast coalitional convergence
to an approximate equilibrium is shown. All our results refer to atomic games (ie players are finite and distinct).

Abstract: The domain of smart cities is currently burgeoning, with a lot of potential for scientific and socio-economic innovation gradually being revealed. It is also becoming apparent that cross-discipline research will be instrumental in designing and building smarter cities, where IoT technology is becoming omnipresent. SmartSantander is an FP7 project that built a massive
city-scale IoT testbed aiming to provide both a tool for the research community and a functional system for the local government to implement operational city
services. In this work, we present key smart cities projects, main application domains and representative smart city frameworks that reflect the latest advances in the smart cities domain and our own experience through SmartSantander. The project has deployed 51.910 IoT endpoints, offering a massive infrastructure to the community, as well as functional system services and a number of end-user applications. Based on these aspects, we identify and
discuss a number of key scientific and technological challenges. We also present an overview of the developed system components and applications, and
discuss the ways that current smart city challenges were handled in the project.

Abstract: In large-scale or evolving networks, such as the Internet,
there is no authority possible to enforce a centralized traffic management.
In such situations, Game Theory and the concepts of Nash equilibria
and Congestion Games [8] are a suitable framework for analyzing
the equilibrium effects of selfish routes selection to network delays.
We focus here on layered networks where selfish users select paths to
route their loads (represented by arbitrary integer weights). We assume
that individual link delays are equal to the total load of the link. We
focus on the algorithm suggested in [2], i.e. a potential-based method
for finding pure Nash equilibria (PNE) in such networks. A superficial
analysis of this algorithm gives an upper bound on its time which is
polynomial in n (the number of users) and the sum of their weights. This
bound can be exponential in n when some weights are superpolynomial.
We provide strong experimental evidence that this algorithm actually
converges to a PNE in strong polynomial time in n (independent of the
weights values). In addition we propose an initial allocation of users
to paths that dramatically accelerates this algorithm, compared to an
arbitrary initial allocation. A by-product of our research is the discovery
of a weighted potentialfunction when link delays are exponential to their
loads. This asserts the existence of PNE for these delay functions and
extends the result of

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 potentialfunction 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 potentialfunction 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: A number of Future Internet testbeds are being deployed around the world for research experimentation and development. SmartSantander
is an infrastructure of massive scale deployed inside a city centre. We argue that utilising the concept of participatory sensing can augment the functionality and potential use-cases of such a system and be beneficiary in a number of scenarios. We discuss
the concept of extending SmartSantander with participatory sensing through the use of volunteers¢ smartphones. We report on our design and implementation, which allows for developers to write
their code for Android devices and then deploy and execute on the devices automatically through our system. We have tested our implementation in a number of scenarios in two cities with the help
of volunteers with promising results; the data collected enhance the ones by fixed infrastructure both quantitatively and qualitatively across the cities, while also engaging citizens more directly.

Abstract: Evolutionary dynamics have been traditionally studied in the context of homogeneous populations, mainly described by the Moran process [15]. Recently, this approach has been generalized in [13] by arranging individuals on the nodes of a network (in general, directed). In this setting, the existence of directed arcs enables the simulation of extreme phenomena, where the fixation probability of a randomly placed mutant (i.e. the probability that the offsprings of the mutant eventually spread over the whole population) is arbitrarily small or large. On the other hand, undirected networks (i.e. undirected graphs) seem to have a smoother behavior, and thus it is more challenging to find suppressors/amplifiers of selection, that is, graphs with smaller/greater fixation probability than the complete graph (i.e. the homogeneous population). In this paper we focus on undirected graphs. We present the first class of undirected graphs which act as suppressors of selection, by achieving a fixation probability that is at most one half of that of the complete graph, as the number of vertices increases. Moreover, we provide some generic upper and lower bounds for the fixation
probability of general undirected graphs. As our main contribution, we introduce the natural alternative of the model proposed in [13]. In our new evolutionary model, all individuals interact simultaneously and the result is a compromise between aggressive and non-aggressive individuals. That is, the behavior of the individuals in our new model and in the model of [13] can be interpreted as an “aggregation” vs. an “all-or-nothing” strategy, respectively. We prove that our new model of mutual influences admits a potentialfunction, which guarantees the convergence of the system for any graph topology and any initial fitness vector of the individuals. Furthermore, we prove fast convergence to the stable state for the case of the complete graph, as well as we provide almost tight bounds on the limit fitness of the individuals. Apart from being important on its own, this new evolutionary model appears to be useful also in the abstract modeling of control mechanisms over invading populations in networks. We demonstrate this by introducing and analyzing two alternative control approaches, for which we bound the time needed to stabilize to the “healthy” state of the system.

Abstract: We study network connection games where the nodes of a networ
k perform edge swaps
in order to improve their communication costs. For the model
proposed by [2], in which the selfish
cost of a node is the sum of all shortest path distances to the o
ther nodes, we use the probabilistic
method to provide a new, structural characterization of equ
ilibrium graphs. We show how to use this
characterization in order to prove upper bounds on the diame
ter of equilibrium graphs in terms of the
size of the largest
k
-vicinity (defined as the the set of vertices within distance
k
from a vertex), for
any
k
≥
1 and in terms of the number of edges, thus settling positivel
y a conjecture of [2] in the cases
of graphs of large
k
-vicinity size (including graphs of large maximum degree) a
nd of graphs which are
dense enough.
Next, we present a new swap-based network creation game, in w
hich selfish costs depend on the imme-
diate neighborhood of each node; in particular, the profit of
a node is defined as the sum of the degrees
of its neighbors. We prove that, in contrast to the previous m
odel, this network creation game admits
an exact potential, and also that any equilibrium graph cont
ains an induced star. The existence of the
potentialfunction is exploited in order to show that an equi
librium can be reached in expected polyno-
mial time even in the case where nodes can only acquire limite
d knowledge concerning non-neighboring
nodes.