Coverage Capacity Optimization for Mobile Sensor Networks Based on Evolutionary Games

The optimal and distributed provisioning of high coverage capacity in mobile sensor networks is known as a fundamental but hard problem. The situation is exacerbated in a mobile wireless setting due to the dynamic coverage of a mobile sensor network resulting from continuous movement of sensors. In this paper, we propose an optimization framework for maximizing the coverage capacity in mobile sensor networks that comprise both stationary sensors (SSs) and mobile sensors (MSs). Both the intracoverage capacity and the intercoverage capacity are jointly optimized by considering the control of the power and distance between MSs and SSs and the interference among MSs. We propose a new noncooperative control algorithm that iteratively solves intracoverage capacity optimization between MSs and SSs. We also further formulate intercoverage capacity as evolutionary coalition game and present a new cooperative interference control algorithm that iteratively solves intercoverage capacity optimization among MSs. We prove the existence of a solution for iteration control equation of the power and distance and the interference to maximize the coverage capacity. Finally, we assess the performance of the proposed algorithm and show that proposed control scheme can effectively improve the average coveragecapacity in mobile sensor networks.