Node optimization coverage method under link model in passive monitoring system of three-dimensional wireless sensor network

被引:10
作者
Hao, Zhanjun [1 ,2 ]
Qu, Nanjiang [1 ]
Dang, Xiaochao [1 ,2 ]
Hou, Jiaojiao [1 ]
机构
[1] Northwest Normal Univ, Coll Comp Sci & Engn, Lanzhou 730070, Gansu, Peoples R China
[2] Gansu Prov Internet Things Engn Res Ctr, Lanzhou, Gansu, Peoples R China
基金
中国国家自然科学基金;
关键词
Wireless sensor network; three-dimensional coverage; link model; received signal strength indicator; coverage verification; TARGET COVERAGE;
D O I
10.1177/1550147719869877
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
3D coverage is not only closer to the actual application environment, but also a research hotspot of sensor networks in recent years. For this reason, a node optimization coverage method under link model in passive monitoring system of three-dimensional wireless sensor network is proposed in this article. According to wireless link-aware area, the link coverage model in three-dimensional wireless sensor network is constructed, and the cube-based network coverage is used to represent the quality of service of the network. This model takes advantage of the principle that the presence of human beings can change the transmission channel of the link. On this basis, the intruder is detected by the data packets transmitted between the wireless links, and then the coverage area is monitored by monitoring the received signal strength of the wireless signal. Based on this new link awareness model, the problem of optimal coverage deployment of the receiving node is solved, that is, how to deploy the receiving node to achieve the optimal coverage of the monitoring area when the location of the sending node is given. In the process of optimal coverage, the traditional genetic algorithm and particle swarm optimization algorithm are introduced and improved. Based on the genetic algorithm, the particle swarm optimization algorithm which integrates the idea of simulated annealing is regarded as an important operator of the genetic algorithm, which can converge to the optimal solution quickly. The simulation results show that the proposed method can improve the network coverage, converge quickly, and reduce the network energy consumption. In addition, we set up a real experimental environment for coverage verification, and the experimental results verify the feasibility of the proposed method.
引用
收藏
页码:1 / 16
页数:16
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