北京邮电大学学报

  • EI核心期刊

北京邮电大学学报 ›› 2012, Vol. 35 ›› Issue (5): 26-30.doi: 10.13190/jbupt.201205.26.qinzhch

• 论文 • 上一篇    下一篇

利用粒子群优化的WSN环状簇路由协议

秦智超, 周 正, 赵小川   

  1. 泛网无线通信教育部重点实验室(北京邮电大学)
  • 收稿日期:2011-12-23 修回日期:2012-06-07 出版日期:2012-10-28 发布日期:2012-07-06
  • 通讯作者: 秦智超 E-mail:qinzhichao@bupt.edu.cn
  • 作者简介:秦智超(1981-),男,博士生,Email:qinzhichao@bupt.edu.cn 周 正(1945-),男,教授,博士生导师
  • 基金资助:

    国家科技重大专项项目(2009ZX03006-009);韩国知识经济部仁荷大学ITRC基金项目(NIPA-2011-C1090-1111-0007)

A Ring-Based Clustering Routing Protocol for WSN Using Particle Swarm Optimization

QIN Zhi-chao, ZHOU Zheng, ZHAO Xiao-chuan   

  1. Key Laboratory of Universal Wireless Communication (Beijing University of Posts and Telecommunications), Ministry of Education
  • Received:2011-12-23 Revised:2012-06-07 Online:2012-10-28 Published:2012-07-06
  • Contact: Zhi-Chao QIN E-mail:qinzhichao@bupt.edu.cn

摘要:

针对无线传感器网络(WSN)中采用多跳分簇算法所带来的能耗不均衡问题,提出了一种利用粒子群优化的环状簇路由协议. 该协议采用粒子群算法将整个网络划分成间隔不等的同心圆,在各环内再分成若干扇区作为簇首选举的基本单位. 在每个扇区内,各节点根据到扇区中心的距离剩余能量来竞选簇首. 同时引入能级的概念,在很大程度上克服了簇首轮换速度过快造成网络开销过大以及轮换速度过慢造成单个节点过早死亡的缺点. 仿真结果表明,该协议有效地均衡了各环间的能耗,延长了网络寿命.

关键词: 无线传感器网络, 粒子群优化, 非均匀分簇, 能量均衡

Abstract:

In order to solve the uneven energy consumption caused by typical clustering routing using multi-hop transmission in wireless sensor networks(WSN), a ring-based clustering routing protocol for WSN using particle swarm optimization is proposed. The entire region is divided into a number of concentric circles with different intervals. Each ring contains many sectors regarded as the basic unit for cluster head selection. And each node runs for cluster head according to the distance to the center of sector and its residual energy. Meanwhile, the energy level mechanism is introduced to overcome the weaknesses that the network overhead is too large when the cluster head rotation speed is too fast and a single node dies prematurely when the cluster head rotation speed is too slow. Simulation shows that this protocol can effectively balance the energy consumption among the rings, and extend the network lifetime.

Key words: wireless sensor networks, particle swarm optimization, uneven clustering, energy balance

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