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.
CITATION STYLE
Zhu, B., Suzuki, J., & Boonma, P. (2012). Evolutionary and noise-aware data gathering for wireless sensor networks. In Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering (Vol. 87 LNICST, pp. 32–39). https://doi.org/10.1007/978-3-642-32615-8_5
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