Clone Chaotic Niche Evolutionary Algorithm for Duty Cycle Control Optimization in Wireless Multimedia Sensor Networks

One of the most interesting issue regarding to wireless multimedia sensor networks (WMSNs) is to maximizing the network lifetime. Because sensor nodes are constrained in energy, it is very important and necessary to exploit novel duty cycle design algorithms. Such a problem is important in improving network lifetime in WMSNs. The new contribution of our paper is that we propose a clone chaotic niche evolutionary algorithm (CCNEA) for duty cycle design problem in WMSNs. Novel clone operator and chaotic operator have been designed to develop solutions randomly. The strategy merges the merits of clone selection, chaotic generation, and niche operator. CCNEA is a style of swarm algorithm, which has strong global exploit ability. CCNEA utilizes chaotic generation approach which targets to avoid local optima. Then, simulations are performed to verify the robust and efficacy performance of CCNEA compared to methods according to particle swarm optimization (PSO) and quantum genetic algorithm (QGA) under an WMSNs conditions. Simulation experiments denote that the presented CCNEA outperforms PSO and QGA under different conditions, especially for WMSNs that has large number of sensors.