文献类型：期刊文献

英文题名：Wireless sensor network node optimal coverage based on improved genetic algorithm and binary ant colony algorithm

作者：Tian, Jingwen[1];Gao, Meijuan[1];Ge, Guangshuang[1]

通讯作者：Tian, JW[1]

机构：[1]Beijing Union Univ, Coll Informat Technol, Beijing 100101, Peoples R China

第一机构：北京联合大学智慧城市学院

通讯机构：[1]corresponding author), Beijing Union Univ, Coll Informat Technol, Beijing 100101, Peoples R China.|[1141734]北京联合大学智慧城市学院;[11417]北京联合大学;

年份：2016

卷号：2016

期号：1

外文期刊名：EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING

收录：;EI(收录号：20161702281354);Scopus(收录号：2-s2.0-84963730219);WOS:【SCI-EXPANDED(收录号:WOS:000374285400002)】；

基金：This work is supported in part by the National Natural Science Foundation of China under Grant No. 61271370, the National High Technology Research and Development Program of China (863 Program) under Grant No. 2013AA013202, and Funding Project for Academic Human Resources Development in Beijing Union University No. 11101501105.

语种：英文

外文关键词：Wireless sensor network; Node optimal coverage; Genetic algorithm; Binary ant colony algorithm

摘要：Considering the situation of some practical factors such as energy saving of the nodes and the high density of distributing nodes in wireless sensor networks, a wireless sensor network (WSN) node optimal coverage method based on improved genetic algorithm and binary ant colony algorithm is proposed in this paper. The genetic algorithm and ant colony algorithm are improved and fused aiming at their disadvantages. The binary code expects a low intelligence of each ant, and each path corresponds to a comparatively small storage space, thus considerably improving the efficiency of computation. The optimal working node set is computed according to the max-coverage area of working sensor and the min-number of working sensor constraint conditions to optimize algorithm. The simulation results demonstrate that the proposed algorithm can converge at the optimal solution fast and satisfy the requirement of low node utilization rate and a high coverage rate, thus prolonging the network lifetime efficiently.