Sensing Radius Adjustment in Wireless Sensor Networks: A Game Theoretical Approach

Wireless sensor networks consist of a collection of sensor nodes deployed densely and randomly to fully cover a set of targets. Due to high redundancy incurred, it is possible to both preserve energy and enhance coverage quality by first switching off some sensors and then adjusting the sensing radius of the remaining ones. In this paper, the problem of target coverage in wireless sensor networks is studied by keeping a small number of active sensor nodes and adjusting the sensing radius of nodes. We propose a new game theory-based algorithm to target coverage. Inspired by current challenges in energy-limited sensor networks, we formulate the target coverage problem with adjustable sensing range as a repeated multiplayer game in which a utility function is formulated to consider the tradeoff between energy consumption and coverage quality. To solve the formulated game and achieve the Nash equilibrium, we present a distributed payoff based learning algorithm where each sensor only remembers its utility values and actions played during the last plays. The simulation results demonstrate the performance of our proposed game-theoretic algorithm and its superiority over previous approaches in terms of increasing the coverage rate and reducing the number of active nodes.