Energy-efficient Clustering Routing Protocol for Wireless Sensor Networks Based on Virtual Force

被引：0
|
作者：
Zhao X.-Q. [1 ,3 ]
Cui Y.-P. [2 ]
Guo Z. [1 ,3 ]
Liu M. [1 ,3 ]
Li X. [1 ,3 ]
Wen Q. [1 ,3 ]
机构：
[1] School of Communication and Information Engineering, Xi'an University of Posts and Telecommunications, Xi'an
[2] Key Laboratory of Universal Wireless Communications, Ministry of Education (Beijing University of Posts and Telecommunications), Beijing
[3] Shaanxi Key Laboratory of Information Communication Network and Security (Xi'an University of Posts and Telecommunications), Xi'an
来源：
Ruan Jian Xue Bao/Journal of Software | 2022年 / 33卷 / 02期
关键词：
Clustering routing protocol; Optimal number of cluster heads; Virtual force; Wireless sensor networks (WSNs);
D O I：
10.13328/j.cnki.jos.006159
中图分类号：
学科分类号：
摘要：
As one of the key technologies of wireless sensor networks (WSNs), clustering routing protocol has gradually become a research hotspot of WSNs routing protocol due to its advantages of strong scalability and low energy consumption. How to select the optimal cluster head is the key to improve the performance of cluster routing protocol. In this study, by revealing the mapping relationship among cluster head number and the network energy consumption in different scenarios, with the goal of minimizing energy consumption, the calculation theory of optimal number of cluster heads is constructed. The conditions of using multi-hop strategy among clusters are discussed for different scale networks; the concept of virtual cluster head and its three virtual force models is proposed. Three virtual force models between virtual cluster head and boundaries, node and other virtual cluster heads are constructed, and the optimal distance thresholds for different virtual forces and the differences are discussed. In order to realize the minimization and equalization of network energy consumption, the fitness function of residual energy and distance factor is set up to form an energy efficient routing protocol based on virtual force. The experimental results show that in networks of various scales, compared with the fitness-value based improved gray wolf optimizer, the improved low-energy adaptive clustering hierarchy protocol and the modified distributed energy efficient clustering algorithm, the algorithm proposed in this study makes the cluster head more uniform, the node energy consumption lower and more balanced, and the network life is effectively extended. © Copyright 2022, Institute of Software, the Chinese Academy of Sciences. All rights reserved.
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页码：622 / 640
页数：18
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