Low-energy dynamic clustering scheme for multi-layer wireless sensor networks. (May 2021)

• Record Type: Journal Article
• Authors: Liu, Xingchun; Yu, Jingjing; Zhang, Wenqi; Tian, Hui
• Is Part Of: Computers & electrical engineering. Volume 91(2021)
• Publication Date: 2021-05
• Subjects: Dynamic clustering -- Low-energy consumption -- Fuzzy logic -- Homogeneous WSNs -- Heterogeneous WSNs; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2021.107093
• Languages: English
• ISSNs: 0045-7906

Abstract

Highlights: Whether it is a homogeneous WSNs or a heterogeneous WSNs, the cluster head selection scheme is extremely important and will affect the performance of the entire network. The traditional LEACH clustering scheme and DEEC clustering scheme only consider the remaining energy of the node or the initial energy of the node when selecting the cluster head. This paper comprehensively considers the remaining energy of the node, the relative density of the node, and the relative distance between the node and the base station to generate the probability of the node being elected as the cluster head. This paper considers an improved low-energy dynamic clustering scheme based on fuzzy logic to balance the energy consumption of the network and prolong the lifetime of network. A low-power dynamic clustering scheme based on fuzzy logic provides an effective method for multi-layer clustering networks. Abstract: It is inconvenient to replace the sensor nodes with limited energy in wireless sensor networks (WSNs) when they are deployed in remote or dangerous monitoring area, that makes energy consumption become the main issue to limit wide application of WSNs. Existing clustering methods only consider heterogeneity of node energy for head selection, irrespective of differences in network structure and node density. Fuzzy logic scheme is applied in this paper to consider multiple factors clustering with the purpose of prolonging network lifetime. In addition to the initial energy, the relative density of nodes and the relative distance between nodes and base station are considered to select the cluster head dynamically. Experimental results have demonstrated that the proposed dynamic clustering scheme can balance the energy consumption of the nodes in both homogeneous and heterogeneous networks, effectively prolong the lifetime of the network, maintain the accuracy of data aggregation. Graphical abstract: Image, graphical abstract