基于自适应剩余能量阈值的WSN蚁群路由算法  

An adaptive threshold of remaining energy based ant colony routing algorithm

作　　者：王恭[1] 孙铭阳 孙汇阳 张叶[1] 滕子铭 WANG Gong;SUN Mingyang;SUN Huiyang;ZHANG Ye;TENG Ziming(School of Automation Engineering, Northeast Electric Power University, Jilin 132012, China;Department of Cryptographic Science and Technology, Beijing Electronic Science and Technology Institute, Beijing 100070, China;College of Communications Engineering, Jilin University, Changchun 130012, China)

机构地区：[1]东北电力大学自动化工程学院,吉林吉林132012 [2]北京电子科技学院密码科学与技术系,北京100070 [3]吉林大学通信工程学院,吉林长春130012

出　　处：《西北工业大学学报》2022年第2期442-449,共8页Journal of Northwestern Polytechnical University

基　　金：国家重点研发计划项目(2018YFB1500800);吉林省科技厅技术攻关项目(20190303023SF);国家电网科技合作项目(SGTJDK00DYJS2000148)资助。

摘　　要：针对无线传感器网络中节点能量分布不均衡和路由算法陷入局部最优解等问题,提出一种基于自适应剩余能量阈值的WSN蚁群路由算法(ATRE-ARA),引入搜索角修正信息素启发函数,对搜索路径进行限制,降低节点能量开销;将节点剩余能量阈值自适应化,改进信息素增量公式,设置信息素浓度上限与下限,优化信息素更新策略,提高信息素增量的准确性,在平衡网络中节点剩余能量的同时提高全局寻优能力。仿真实验表明,ATRE-ARA算法在2种环境下节点平均能耗与ARA算法相比降低了15.12%和11.68%,最优路径长度与EEABR算法相比分别缩短了1.47%和1.59%,证明该算法可有效平衡全局网络能耗,提升算法搜索全局最优的能力,延长网络生命周期。Because the node energy distribution among wireless sensor networks is not balanced and their routing algorithm is trapped in local optimal solution,this paper proposes the ant colony routing algorithm for wireless sensor network based on the adaptive residual energy threshold(ATRE-ARA).It introduces the search angle correction pheromone heuristic function to limit the search path and to reduce node energy costs.The residual energy threshold of the node is adaptive;the formula of pheromone increment is improved.The upper and lower limits of pheromone concentration are set;the pheromone updating strategy is optimized,thereby improving the accuracy of pheromone increment and the global optimization capability and balancing the residual energy of nodes in the wireless sensor network.The simulation results show that the ant colony routing algorithm reduces its average energy consumption by 15.12%and 11.68%in two environments and that its optimal path length is shortened by 1.47%and 1.59%,respectively,thus proving that the algorithm can effectively balance the global network energy consumption,improving the capability of the algorithm to search for global optimal solutions and extending the life cycle of the wireless sensor network.

关 键 词：无线传感器网络 能量阈值 蚁群算法 搜索角 信息素浓度 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]