Coverage Optimization of Sensors under Multiple Constraints Using the Improved PSO Algorithm. (22nd September 2020)

• Record Type: Journal Article
• Authors: Ling, Haifeng; Zhu, Tao; He, Weixiong; Luo, Hongchuan; Wang, Qing; Jiang, Yi
• Other Names: Shao Xingling Academic Editor.
• Is Part Of: Mathematical problems in engineering. Volume 2020(2020)
• Publication Date: 2020-09-22
• Subjects: Engineering mathematics -- Periodicals; 510.2462
• DOI: 10.1155/2020/8820907
• Languages: English
• ISSNs: 1024-123X

Abstract

Abstract : Sensor deployment is an important issue in wireless sensor network (WSN), which is a typical nonlinear system. Conditions of both area coverage and point coverage should be considered in research studies on sensor coverage. It is generally necessary to ensure high coverage ratio of area when controlling sensor locations, and covering specific point targets to ensure long lifetime is also important sometimes. In current studies, swarm intelligence algorithms such as particle swarm optimization (PSO) are widely used to solve the sensor deployment problem in WSN. In this paper, coverage rate and network life indicators are analyzed comprehensively with establishment of a more general K-coverage model. In related calculation examples with different coverage requirements including target coverage, area coverage, and boundary coverage, several improved algorithms based on PSO are applied to solve the problem in the paper. Simulation results show that the improved algorithms can achieve a good performance and deployment effect.