基于改进混合蛙跳的移动传感网络拓扑结构优化研究  

Research on Topology Optimization of Mobile Sensor Networks Based on Improved Shuffled Frog Leap

作　　者：蔡绍堂 乐英高[1,2] 胡骏 麻硕琪 曹莉[1] CAI Shao-tang;YUE Ying-gao;HU Jun;MA Shuo-qi;CAO Li(Artificial Intelligence Key Laboratory of Sichuan Province,Sichuan University of Science and Engineering,Zigong 643000,China;Material Corrosion and Protection Key Laboratory of Sichuan Province,Sichuan University of Science and Engineering,Zigong 643000,China;Mechanical Engineering Institute,Sichuan University of Science and Engi-neering,Zigong 643000,China)

机构地区：[1]四川理工学院人工智能四川省重点实验室,自贡643000 [2]四川理工学院材料腐蚀与防护四川省重点实验室,自贡643000 [3]四川理工学院机械工程学院,自贡643000

出　　处：《自动化与仪表》2018年第8期89-93,108,共6页Automation & Instrumentation

基　　金：国家自然科学基金项目(11705122);人工智能四川省重点实验室开放基金项目(2017RYJ01);四川理工学院人才引进项目(2017RCL10);四川省教育厅项目(18ZB0418)

摘　　要：该文提出了一种基于改进混合蛙跳算法的移动传感网络拓扑结构优化设计。该改进算法重新设计了群组内更新策略,采用随机双向更新策略,采用同一概率周期性随机选择簇头。通过算法仿真和结果分析,改进混合蛙跳算法与混沌量子粒子群算法、混沌人工蜂群算法相比,在网络总能耗、负载均衡率、分组平均投递率、网络覆盖率、网络存活节点个数等方便表现其优越性,其中剩余平均能量比CQPSO、CABC提高了20%和9%。This paper proposes a mobile sensor network topology optimization design based on improved shuffled frog leaping algorithm. The improved algorithm redesigns the intra-group update strategy,and adopts a random bidirectional update strategy,using the same probability periodic random selection of cluster heads. Through algorithm simulation and result analysis,the improved shuffled frog leaping algorithm compared with chaotic quantum particle swarm optimization algorithm and chaotic artificial bee colony algorithm in the total network energy consumption,load balancing ratio,average packet delivery rate,network coverage rate,network survival node The number of such advantages facilitates the superiority of the performance,in which the remaining average energy is increased by 20% and 9% over CQPSO and CABC.

关 键 词：无线传感网络 混合蛙跳算法 更新策略 最优覆盖 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]