A game theoretic framework for bandwidth allocation and pricing in broadband networks
IEEE/ACM Transactions on Networking (TON)
A utility-based power-control scheme in wireless cellular systems
IEEE/ACM Transactions on Networking (TON)
Integrated coverage and connectivity configuration for energy conservation in sensor networks
ACM Transactions on Sensor Networks (TOSN)
Nash Equilibria of Packet Forwarding Strategies in Wireless Ad Hoc Networks
IEEE Transactions on Mobile Computing
Target Coverage With QoS Requirements in Wireless Sensor Networks
IPC '07 Proceedings of the The 2007 International Conference on Intelligent Pervasive Computing
An Efficient Approach for Point Coverage Problem of Sensor Network
ISECS '08 Proceedings of the 2008 International Symposium on Electronic Commerce and Security
Q-Coverage Problem in Wireless Sensor Networks
ICDCN '09 Proceedings of the 10th International Conference on Distributed Computing and Networking
IEEE/ACM Transactions on Networking (TON)
Non-Cooperative Resource Competition Game by Virtual Referee in Multi-Cell OFDMA Networks
IEEE Journal on Selected Areas in Communications
Optimality and Complexity of Pure Nash Equilibria in the Coverage Game
IEEE Journal on Selected Areas in Communications
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Wireless sensor nodes are usually densely deployed to completely cover (monitor) a set of targets. Consequently, redundant sensor nodes that are not currently needed in the covering task can be powered off to conserve energy. These sensors can take over the covering task later to prolong network lifetime. The coverage problem, concerns picking up a set of working sensors that collectively meet the coverage requirements. The problem is complicated by the possibility that targets may have different coverage requirements while sensor nodes may have different amounts of energy. This article proposes a game-theoretic approach to the coverage problem, where each sensor autonomously decides its state with a simple rule based on local information. We give rigorous proofs to show stability, correctness, and efficiency of the proposed game. Implementation variants of the game consider specific issues, such as game convergence time and different amounts of sensor energy. Simulation results show significant improvement in network lifetime by the proposed approach when compared with representative alternatives.