Evolutionary and noise-aware data gathering for wireless sensor networks

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. © 2012 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering.