Minimization of the Redundant Coverage for Dense Wireless Sensor Networks

Abstract

Density control is a promising method to conserve system energy and prolonging lifetime of wireless sensor networks. In this paper, we address the issue of maintaining sensing coverage of surveillance target in large density wireless sensor networks and present an efficient technique for the selection of active sensor nodes. First, the At Most k-Coverage Problem (AM k-Coverage) is defined and modeled as a nonlinear integer programming. Second, Genetic Algorithm which is a quasi-parallel method to construct set cover is designed to solve the multi-objective nonlinear integer programming. And later by using Genetic Algorithm, a central algorithm is designed to organize a sensor network into coverage sets. Finally, Experimental results show that the proposed algorithm can construct the coverage sets reliably and reduce the number of active sensor nodes which is helpful to reduce system energy consumption and prolong the network lifespan.