1,840 research outputs found
Hedonic Coalition Formation for Distributed Task Allocation among Wireless Agents
Autonomous wireless agents such as unmanned aerial vehicles or mobile base
stations present a great potential for deployment in next-generation wireless
networks. While current literature has been mainly focused on the use of agents
within robotics or software applications, we propose a novel usage model for
self-organizing agents suited to wireless networks. In the proposed model, a
number of agents are required to collect data from several arbitrarily located
tasks. Each task represents a queue of packets that require collection and
subsequent wireless transmission by the agents to a central receiver. The
problem is modeled as a hedonic coalition formation game between the agents and
the tasks that interact in order to form disjoint coalitions. Each formed
coalition is modeled as a polling system consisting of a number of agents which
move between the different tasks present in the coalition, collect and transmit
the packets. Within each coalition, some agents can also take the role of a
relay for improving the packet success rate of the transmission. The proposed
algorithm allows the tasks and the agents to take distributed decisions to join
or leave a coalition, based on the achieved benefit in terms of effective
throughput, and the cost in terms of delay. As a result of these decisions, the
agents and tasks structure themselves into independent disjoint coalitions
which constitute a Nash-stable network partition. Moreover, the proposed
algorithm allows the agents and tasks to adapt the topology to environmental
changes such as the arrival/removal of tasks or the mobility of the tasks.
Simulation results show how the proposed algorithm improves the performance, in
terms of average player (agent or task) payoff, of at least 30.26% (for a
network of 5 agents with up to 25 tasks) relatively to a scheme that allocates
nearby tasks equally among agents.Comment: to appear, IEEE Transactions on Mobile Computin
Physical Layer Security: Coalitional Games for Distributed Cooperation
Cooperation between wireless network nodes is a promising technique for
improving the physical layer security of wireless transmission, in terms of
secrecy capacity, in the presence of multiple eavesdroppers. While existing
physical layer security literature answered the question "what are the
link-level secrecy capacity gains from cooperation?", this paper attempts to
answer the question of "how to achieve those gains in a practical decentralized
wireless network and in the presence of a secrecy capacity cost for information
exchange?". For this purpose, we model the physical layer security cooperation
problem as a coalitional game with non-transferable utility and propose a
distributed algorithm for coalition formation. Through the proposed algorithm,
the wireless users can autonomously cooperate and self-organize into disjoint
independent coalitions, while maximizing their secrecy capacity taking into
account the security costs during information exchange. We analyze the
resulting coalitional structures, discuss their properties, and study how the
users can self-adapt the network topology to environmental changes such as
mobility. Simulation results show that the proposed algorithm allows the users
to cooperate and self-organize while improving the average secrecy capacity per
user up to 25.32% relative to the non-cooperative case.Comment: Best paper Award at Wiopt 200
Computational Intelligence Inspired Data Delivery for Vehicle-to-Roadside Communications
We propose a vehicle-to-roadside communication protocol based on distributed clustering where a coalitional game approach is used to stimulate the vehicles to join a cluster, and a fuzzy logic algorithm is employed to generate stable clusters by considering multiple metrics of vehicle velocity, moving pattern, and signal qualities between vehicles. A reinforcement learning algorithm with game theory based reward allocation is employed to guide each vehicle to select the route that can maximize the whole network performance. The protocol is integrated with a multi-hop data delivery virtualization scheme that works on the top of the transport layer and provides high performance for multi-hop end-to-end data transmissions. We conduct realistic computer simulations to show the performance advantage of the protocol over other approaches
Game-theoretic Resource Allocation Methods for Device-to-Device (D2D) Communication
Device-to-device (D2D) communication underlaying cellular networks allows
mobile devices such as smartphones and tablets to use the licensed spectrum
allocated to cellular services for direct peer-to-peer transmission. D2D
communication can use either one-hop transmission (i.e., in D2D direct
communication) or multi-hop cluster-based transmission (i.e., in D2D local area
networks). The D2D devices can compete or cooperate with each other to reuse
the radio resources in D2D networks. Therefore, resource allocation and access
for D2D communication can be treated as games. The theories behind these games
provide a variety of mathematical tools to effectively model and analyze the
individual or group behaviors of D2D users. In addition, game models can
provide distributed solutions to the resource allocation problems for D2D
communication. The aim of this article is to demonstrate the applications of
game-theoretic models to study the radio resource allocation issues in D2D
communication. The article also outlines several key open research directions.Comment: Accepted. IEEE Wireless Comms Mag. 201
Network Formation Games Among Relay Stations in Next Generation Wireless Networks
The introduction of relay station (RS) nodes is a key feature in next
generation wireless networks such as 3GPP's long term evolution advanced
(LTE-Advanced), or the forthcoming IEEE 802.16j WiMAX standard. This paper
presents, using game theory, a novel approach for the formation of the tree
architecture that connects the RSs and their serving base station in the
\emph{uplink} of the next generation wireless multi-hop systems. Unlike
existing literature which mainly focused on performance analysis, we propose a
distributed algorithm for studying the \emph{structure} and \emph{dynamics} of
the network. We formulate a network formation game among the RSs whereby each
RS aims to maximize a cross-layer utility function that takes into account the
benefit from cooperative transmission, in terms of reduced bit error rate, and
the costs in terms of the delay due to multi-hop transmission. For forming the
tree structure, a distributed myopic algorithm is devised. Using the proposed
algorithm, each RS can individually select the path that connects it to the BS
through other RSs while optimizing its utility. We show the convergence of the
algorithm into a Nash tree network, and we study how the RSs can adapt the
network's topology to environmental changes such as mobility or the deployment
of new mobile stations. Simulation results show that the proposed algorithm
presents significant gains in terms of average utility per mobile station which
is at least 17.1% better relatively to the case with no RSs and reaches up to
40.3% improvement compared to a nearest neighbor algorithm (for a network with
10 RSs). The results also show that the average number of hops does not exceed
3 even for a network with up to 25 RSs.Comment: IEEE Transactions on Communications, vol. 59, no. 9, pp. 2528-2542,
September 201
Offloading Content with Self-organizing Mobile Fogs
Mobile users in an urban environment access content on the internet from
different locations. It is challenging for the current service providers to
cope with the increasing content demand from a large number of collocated
mobile users. In-network caching to offload content at nodes closer to users
alleviate the issue, though efficient cache management is required to find out
who should cache what, when and where in an urban environment, given nodes
limited computing, communication and caching resources. To address this, we
first define a novel relation between content popularity and availability in
the network and investigate a node's eligibility to cache content based on its
urban reachability. We then allow nodes to self-organize into mobile fogs to
increase the distributed cache and maximize content availability in a
cost-effective manner. However, to cater rational nodes, we propose a coalition
game for the nodes to offer a maximum "virtual cache" assuming a monetary
reward is paid to them by the service/content provider. Nodes are allowed to
merge into different spatio-temporal coalitions in order to increase the
distributed cache size at the network edge. Results obtained through
simulations using realistic urban mobility trace validate the performance of
our caching system showing a ratio of 60-85% of cache hits compared to the
30-40% obtained by the existing schemes and 10% in case of no coalition
Pilot Clustering in Asymmetric Massive MIMO Networks
We consider the uplink of a cellular massive MIMO network. Since the spectral
efficiency of these networks is limited by pilot contamination, the pilot
allocation across cells is of paramount importance. However, finding efficient
pilot reuse patterns is non-trivial especially in practical asymmetric base
station deployments. In this paper, we approach this problem using coalitional
game theory. Each cell has its own unique pilots and can form coalitions with
other cells to gain access to more pilots. We develop a low-complexity
distributed algorithm and prove convergence to an individually stable coalition
structure. Simulations reveal fast algorithmic convergence and substantial
performance gains over one-cell coalitions and full pilot reuse.Comment: Published in Proc. of IEEE International Workshop on Signal
Processing Advances in Wireless Communications (SPAWC '15), 5 pages, 1
tables, 5 figure
- …