WSN中基于改进蚁群的能量优化路由算法  

Energy Optimized Routing Algorithm Based on Improved Ant Colony in WSN

作　　者：蒋占军[1] 周涛 杨永红 JIANG Zhanjun;ZHOU Tao;YANG Yonghong(School of Electronic and Information Engineering,Lanzhou Jiaotong University,Lanzhou 730070,China)

机构地区：[1]兰州交通大学电子与信息工程学院,兰州730070

出　　处：《计算机工程》2020年第4期189-197,共9页Computer Engineering

基　　金：甘肃省高等学校协同创新团队项目(2017C-09);兰州交通大学百名青年优秀人才培养计划(152220232)。

摘　　要：无线传感器网络存在能耗不均的问题,且Sink节点周围的“热”节点会因负载重而过早死亡.针对该问题,提出一种改进蚁群的能量优化路由算法.在节点分布过程中,采用距离带、限制搜索角和距离因子相结合的方法降低节点能量消耗,同时引入激励机制,剔除优选路径上“热”节点中剩余能量较低且路径较长的节点,利用能量充足且跳数较少的节点来均衡“热”节点的传输任务.在此基础上,以一种包含能量因子的伪随机比例规则优化概率转移函数,降低“热”节点失效的概率,增强算法的寻优能力,避免过早陷入局部最优.仿真结果表明,该算法可有效均衡网络能耗,与IEEABR和IARA算法相比,其网络生存周期更长.To address imbalanced energy consumption in Wireless Sensor Network(WSN)and avoid death of overloaded“hot”nodes around the Sink node,this paper proposes an energy optimized routing algorithm for improved ant colony.In node distribution,the algorithm combines distance band and limited search angle with the distance factor to reduce energy consumption of nodes.The incentive mechanism is introduced to remove the“hot”nodes with insufficient residual energy and a longer path from the preferred path,while the nodes with fewer hops and sufficient energy are used to balance the transmission tasks of hot nodes.On this basis,a pseudo random proportional rule that includes energy factors is used to optimize the probability transfer function,which reduces the probability of hot node failure and enhances the optimization ability of the algorithm.Thus the algorithm can avoid falling into an untimely local optimum.Simulation results show that the proposed algorithm can effectively balance network energy consumption.Compared with the IEEABR and IARA algorithms,the algorithm has a longer network lifetime.

关 键 词：蚁群算法 分层带 激励值 伪随机 网络生存周期 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]