8,575 research outputs found
Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey
Wireless sensor networks (WSNs) consist of autonomous and resource-limited
devices. The devices cooperate to monitor one or more physical phenomena within
an area of interest. WSNs operate as stochastic systems because of randomness
in the monitored environments. For long service time and low maintenance cost,
WSNs require adaptive and robust methods to address data exchange, topology
formulation, resource and power optimization, sensing coverage and object
detection, and security challenges. In these problems, sensor nodes are to make
optimized decisions from a set of accessible strategies to achieve design
goals. This survey reviews numerous applications of the Markov decision process
(MDP) framework, a powerful decision-making tool to develop adaptive algorithms
and protocols for WSNs. Furthermore, various solution methods are discussed and
compared to serve as a guide for using MDPs in WSNs
Coalition Formation Games for Distributed Cooperation Among Roadside Units in Vehicular Networks
Vehicle-to-roadside (V2R) communications enable vehicular networks to support
a wide range of applications for enhancing the efficiency of road
transportation. While existing work focused on non-cooperative techniques for
V2R communications between vehicles and roadside units (RSUs), this paper
investigates novel cooperative strategies among the RSUs in a vehicular
network. We propose a scheme whereby, through cooperation, the RSUs in a
vehicular network can coordinate the classes of data being transmitted through
V2R communications links to the vehicles. This scheme improves the diversity of
the information circulating in the network while exploiting the underlying
content-sharing vehicle-to-vehicle communication network. We model the problem
as a coalition formation game with transferable utility and we propose an
algorithm for forming coalitions among the RSUs. For coalition formation, each
RSU can take an individual decision to join or leave a coalition, depending on
its utility which accounts for the generated revenues and the costs for
coalition coordination. We show that the RSUs can self-organize into a
Nash-stable partition and adapt this partition to environmental changes.
Simulation results show that, depending on different scenarios, coalition
formation presents a performance improvement, in terms of the average payoff
per RSU, ranging between 20.5% and 33.2%, relative to the non-cooperative case.Comment: accepted and to appear in IEEE Journal on Selected Areas in
Communications (JSAC), Special issue on Vehicular Communications and Network
Game Theoretic Approaches to Massive Data Processing in Wireless Networks
Wireless communication networks are becoming highly virtualized with
two-layer hierarchies, in which controllers at the upper layer with tasks to
achieve can ask a large number of agents at the lower layer to help realize
computation, storage, and transmission functions. Through offloading data
processing to the agents, the controllers can accomplish otherwise prohibitive
big data processing. Incentive mechanisms are needed for the agents to perform
the controllers' tasks in order to satisfy the corresponding objectives of
controllers and agents. In this article, a hierarchical game framework with
fast convergence and scalability is proposed to meet the demand for real-time
processing for such situations. Possible future research directions in this
emerging area are also discussed
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