Pareto optimal solution for multi-objective optimization in wireless sensor networks

Abstract

A wireless sensor network (WSN) consists of small sensors with limited sensing range, processing capability, and short communication range. The performance of WSNs is determined by multi-objective optimization. However, these objectives are contradictory and impossible to solve optimization problems with a single optimal decision. This paper presents multi-objective optimization approach to optimize the coverage area of sensor nodes, minimize the energy consumption, and maximize the network lifetime and maintaining connectivity between the current deployed sensor nodes. Pareto optimal based approach is used to address conflicting objectives and trade-offs with respect to non-dominance using non-dominating sorting genetic algorithm 2 (NSGA-2). The tools we have used for simulation are: NS2 simulator, tool command language script (TCL) and C language and Aho Weinberger keninghan script (AWK) are used. We have checked the coverage area, packet deliver ratio, and energy consumption of sensor nodes to evaluate the performance of proposed scheme. According to the simulation results, the packet delivery ration is 0.93 and the coverage ratio of sensor to region of interest is 0.65.