Author Login Editor-in-Chief Peer Review Editor Work Office Work

Computer Engineering ›› 2020, Vol. 46 ›› Issue (1): 179-186. doi: 10.19678/j.issn.1000-3428.0053514

Previous Articles     Next Articles

Energy-Optimized Clustering Routing Algorithm Based on Multi-Factors in WSN

TIAN Jiyao, LIU Guangzhong   

  1. School of Information Engineering, Shanghai Maritime University, Shanghai 201306, China
  • Received:2018-12-28 Revised:2019-03-15 Online:2020-01-15 Published:2019-03-27

WSN中基于多因素的能量优化分簇路由算法

田纪尧, 刘广钟   

  1. 上海海事大学 信息工程学院, 上海 201306
  • 作者简介:田纪尧(1994-),男,硕士研究生,主研方向为分布式计算、无线传感器网络;刘广钟,教授、博士。
  • 基金资助:
    国家自然科学基金(61202370);上海市教委科研创新项目(14YZ110);中国博士后科学基金(2014M561512)。

Abstract: In Wireless Sensor Network(WSN),the network nodes only have limited power energy,which greatly affects their service life.Therefore,this paper proposes an energy-optimized clustering routing algorithm based on multiple.First,the optimal cluster head is selected based on fuzzy rule algorithm and the combination of the relative residual energy,the relative centrality and the relative density of nodes.Then,this paper introduces the Theil index to improve the probability function of the ant colony algorithm.On this basis,this paper establishes a linear planning model with a comprehensive consideration of node energy consumption and the quality of communication link.Simulation results show that compared with CFEL,LEACH algorithms,the proposed algorithm can extend network life circle,reduce energy consumption and improve load balancing.

Key words: Wireless Sensor Network(WSN), fuzzy rule, ant colony algorithm, Theil index, loading balancing

摘要: 无线传感器网络中的节点存在电源能量有限的问题,极大地影响了网络节点使用寿命。为此,提出一种基于多因素的能量优化分簇路由算法。通过模糊规则算法并结合节点的相对剩余能量、相对中心度、相对密度选出最优簇首,引入泰尔指数用于改进蚁群算法的概率函数。在此基础上,综合考虑节点能耗与通信链路质量建立线性规划模型。仿真结果表明,与CFEL、LEACH等算法相比,该算法能够延长网络生命周期,降低网络能量消耗,提高网络负载均衡能力。

关键词: 无线传感器网络, 模糊规则, 蚁群算法, 泰尔指数, 负载均衡

CLC Number: