基于PSO优化模糊C均值的WSN分簇路由算法

doi:10.11959/j.issn.1000-436x.2021053

通信学报 ›› 2021, Vol. 42 ›› Issue (3): 91-99.doi: 10.11959/j.issn.1000-436x.2021053

基于PSO优化模糊C均值的WSN分簇路由算法

孙爱晶¹, 李世昌¹, 张艺才²

¹ 西安邮电大学通信与信息工程学院，陕西西安 710121
² 西安邮电大学电子工程学院，陕西西安 710121

修回日期:2021-02-04 出版日期:2021-03-25 发布日期:2021-03-01
作者简介:孙爱晶（1971- ），女，陕西西安人，西安邮电大学教授，主要研究方向为物联网技术、信息安全风险评估技术等。
李世昌（1997- ），男，湖北武汉人，西安邮电大学硕士生，主要研究方向为无线传感器网络。
张艺才（1997- ），男，湖北武汉人，西安邮电大学硕士生，主要研究方向为嵌入式人工智能。
基金资助:
国家自然科学基金资助项目(61502386);国家自然科学基金资助项目(61772418)

WSN clustering routing algorithm based on PSO optimized fuzzy C-means

Aijing SUN¹, Shichang LI¹, Yicai ZHANG²

¹ School of Communication and Information Engineering, Xi’an University of Posts ＆Telecommunications, Xi’an 710121, China
² School of Electronic Engineering, Xi’an University of Posts ＆Telecommunications, Xi’an 710121, China

Revised:2021-02-04 Online:2021-03-25 Published:2021-03-01
Supported by:
The National Natural Science Foundation of China(61502386);The National Natural Science Foundation of China(61772418)

摘要/Abstract

摘要：

针对无线传感器网络节点能量有限、负载不均衡的问题，提出了一种基于粒子群优化模糊C均值的分簇路由算法POFCA。POFCA分别从成簇阶段和数据传输阶段进行了优化。成簇阶段，首先使用粒子群优化算法优化模糊C均值算法，克服了模糊C均值对初始聚类中心的敏感，并根据节点剩余能量和相对距离动态更新簇首，平衡簇内负载。数据传输阶段，基于距离因子、能量因子和节点负载设计了路径评价函数，并使用猫群优化算法为簇首搜寻最优路由路径，在平衡簇首负载的同时又不会加剧中继节点负载。仿真结果表明，与 LEACH 和LEACH-improved算法相比，POFCA能有效地平衡网络负载，降低网络能耗，延长网络生命周期。

关键词: 无线传感器网络, 粒子群优化, 模糊C均值, 猫群优化, 负载均衡

Abstract:

Aimed at the problems of limited energy and unbalanced load in wireless sensor network, POFCA based on particle swarm optimization fuzzy C-means was proposed.POFCA was respectively optimized from the cluster stage and the data transmission stage.In the clustering stage, the particle swarm optimization fuzzy C-means was firstly used to overcome the sensitivity to the initial clustering center.And the cluster head was dynamically updated according to the remaining power and the relative distance of the nodes to balance the network load.Then in the data transfer phase, a path evaluation function was designed based on the distance factor, the energy factor and the nodal load.Besides, the cat swarm optimization was used to search the optimal routing path for the cluster head to balance the load of the cluster head without increasing the load of the relay node.The simulation result shows that compared with algorithms of LEACH and LEACH-improved, POFCA can effectively balance the network load, reduce the energy consumption of nodes and extend the lifetime of the entire network.

Key words: wireless sensor network, particle swarm optimization, fuzzy C-means, cat swarm optimization, load balancing

中图分类号:

TP393

孙爱晶, 李世昌, 张艺才. 基于PSO优化模糊C均值的WSN分簇路由算法[J]. 通信学报, 2021, 42(3): 91-99.

Aijing SUN, Shichang LI, Yicai ZHANG. WSN clustering routing algorithm based on PSO optimized fuzzy C-means[J]. Journal on Communications, 2021, 42(3): 91-99.

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参数	取值
节点数目	100
基站位置	(50,50)
监测范围	100 m×100 m
数据分组长/bit	4 000
控制分组长/bit	100
粒子数	20
网络系数λ	0.7
模糊因子m	2
最优传输距离d_best/m	32
SMP记忆池大小	5
惯性权重w	[0.2,0.9]
E_init /J	0.5
E_elec/(nJ?bit^?1)	50
E_fs/(pJ?(bit?m²)^?1)	10
E_mp/(pJ?(bit?m⁴)^?1)	0.001 3

基于PSO优化模糊C均值的WSN分簇路由算法

WSN clustering routing algorithm based on PSO optimized fuzzy C-means

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