A quantum-inspired evolutionary clustering algorithm for the lifetime problem of wireless sensor network Online publication date: Fri, 17-Mar-2017
by Chun-Wei Tsai; Chun-Ting Kang; Kai-Cheng Hu; Ming-Chao Chiang
International Journal of Internet Technology and Secured Transactions (IJITST), Vol. 6, No. 4, 2016
Abstract: One of the solutions to the lifetime problem of a wireless sensor network (WSN) is to select a sensor as the cluster head (CH) to reduce the transmission cost of the other sensors in a cluster. However, the high computation load will quickly run out of its energy. The most well-known method for selecting the CHs of a WSN is the so-called low energy adaptive clustering hierarchy (LEACH), but it is far from optimal in terms of the energy consumed. On the other hand, some recent studies showed that the quantum-inspired evolutionary algorithm (QEA) can provide a better result than rule-based and metaheuristic algorithms. This paper is, therefore, aimed at applying QEA to the lifetime problem of a WSN. Simulation results show that the proposed algorithm can provide a better result than LEACH and genetic algorithm in terms of the overall energy consumed, especially for complex and large lifetime problems.
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