Game Theory-Based Planning of Nodes in Wireless Sensor Networks for Optimum Coverage With Maximum Battery Life

Abstract

Maximize the coverage is one of the important aspects, in designing the wireless sensor network. One should aim at a nearly optimum coverage rate without reducing the life span of the network. Numerous solutions were suggested for this from which most try to select the least number of nodes as active, while the others remain in the sleep mode to save energy. This approach extends the life span of the network also. Nevertheless, these methods suffer from a lack of mathematical bases for the initial seed node choice in selecting active nodes. In this manuscript, a distributed method is suggested to address the challenge of maximum coverage with maximum network life. The exploitation of the game theory as a mathematical basis for the choice of active nodes is demonstrated in the current manuscript. The basis of the game theory in node planning, is node compete with each other to become active. Node tries to avoid coverage redundancy using the costs of the activation. This cost use number of the active neighbors and the uncovered area. The comparison of the simulation results with the results of the actual network deployed with nodeMCUs is done. We found that the network lifetimes almost doubles from 52 Hours to 98 hours with actual deployment on two nodeMCUs. The suggested method works well for maximum coverage, life span, and energy efficiency. The proposed method also causes a reduction in the redundancy rate.