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内蒙古自治区呼和浩特市赛罕区大学西街235号 邮编: 010021
作者机构:Beihang Univ Sch Aeronaut Beijing 100191 Peoples R China
出 版 物:《IEEE INTERNET OF THINGS JOURNAL》 (IEEE Internet Things J.)
年 卷 期:2018年第5卷第5期
页 面:3521-3532页
核心收录:
学科分类:0810[工学-信息与通信工程] 0808[工学-电气工程] 08[工学] 0812[工学-计算机科学与技术(可授工学、理学学位)]
基 金:Fundamental Research Funds for the China Central Universities [YWF-14-FGC-024 YWF-13-ZY-02]
主 题:Coverage control Internet of Things (IoT) resample particle swarm optimization (RPSO) sensor and actuator networks
摘 要:In this paper, we proposed a novel method to solve the coverage control problem of sensor networks in the Internet of Things (IoT). The coverage control is an important index to evaluate the performance of network services. Ensuring the quality of network services, it is mainly to maximize the coverage of the network and minimize the energy consumption at the same time for the purpose of extending the network life cycle effect. Because of the overlay redundancy, it adopts the sleeping scheduling mechanism of nodes. The optimal solution is obtained after utilizing the coverage rate and the node sleep rate as the optimization objective function. Particle swarm optimization (PSO) is a group intelligent optimization algorithm. In practical applications, PSO often convergence in the local optimal solution prematurely. In order to balance the global search ability and convergence speed of PSO, We have improved the PSO based on the resampling technique, named resampled PSO (RPSO). The RPSO can not only maintain the diversity of the population, which can avoid premature convergence of the algorithm to some extent, but also ensure that each particle is active, reducing the calculation of redundancy, thereby improving the efficiency of the algorithm. The experimental results show that the RPSO can deal with complex multipeak optimization problem efficiently and reliably. Then the RPSO is used to solve the coverage control problem of sensor networks in IoT and has a great performance.