Analysis of Network Coverage Optimization Based on Feedback K-Means Clustering and Artificial Fish Swarm Algorithm

• Published in: IEEE access Vol. 8; pp. 42864 - 42876
• Main Authors: Feng, Yingying, Zhao, Shasha, Liu, Hui
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: algorithm optimization; Algorithms; artificial fish swarm algorithm; Cluster analysis; Clustering; Clustering algorithms; Energy consumption; Energy dissipation; Feedback; Information processing; K-means clustering; Network analysis; network coverage; Optimization; Protocol (computers); Quality of service architectures; Routing; Routing protocols; Sensors; Service life; Vector quantization; Wireless networks; Wireless sensor networks
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2020.2970208

There is a certain energy loss in the process of wireless sensor network information collection. Moreover, the current network protocols and network coverage methods are not sufficient to effectively reduce system energy consumption. In order to improve the operating efficiency and service life of wireless sensor networks, this study analyzes the classic LEACH protocol, summarizes the advantages and disadvantages, and proposes a targeted clustering method based on the K-means algorithm. At the same time, in order to maximize the network coverage and minimize the energy consumption on the basis of ensuring the quality of service, a wireless sensor network coverage optimization method based on an improved artificial fish swarm algorithm was proposed. In addition, a controlled experiment is designed to analyze the effectiveness and practical effects of the proposed algorithm. The experimental results show that the method proposed in this paper has certain advantages over traditional methods and can provide theoretical references for subsequent related research.