Evolutionary and Noise-Aware Data Gathering for Wireless Sensor Networks

Abstract

Abstract. This paper formulates a prioritized data gathering problem in noisy wireless sensor networks (WSNs) and solves the problem with a noise-aware evolutionary multiobjective optimization algorithm (EMOA). Unlike existing local search heuristics, the proposed algorithm can seek the Pareto-optimal routing structures with respect to conflicting optimization objectives. Simulation results demonstrate that the proposed algorithm outperforms a traditional EMOA in a noisy WSN.