基于扇形链路策略的改进蚁群分簇路由协议  

Improved ant colony clustering routing protocol based on sector link policy

作　　者：王丽芳[1] 杨康杰 郭晓东[2] 张哲 WANG Li-fang;YANG Kang-jie;GUO Xiao-dong;ZHANG Zhe(School of Computer Science and Technology,Taiyuan University of Science and Technology,Taiyuan 030024,China;School of Electronic Information Engineering,Taiyuan University of Science and Technology,Taiyuan 030024,China)

机构地区：[1]太原科技大学计算机科学与技术学院,山西太原030024 [2]太原科技大学电子信息工程学院,山西太原030024

出　　处：《计算机工程与设计》2024年第9期2620-2626,共7页Computer Engineering and Design

基　　金：国家自然科学基金项目(61876123);太原科技大学博士科研启动基金项目(20212021);山西省研究生教育教学改革基金项目(2021YJJG238);山西省研究生优秀创新基金项目(2021Y697);太原科技大学研究生优秀创新基金项目(SY2022060、XCX212081)。

摘　　要：针对网络覆盖区域较大、节点数量较多的无线传感器网络,容易出现部分节点过早死亡等情况,提出一种基于扇形链路策略的改进蚁群分簇路由协议RACO-SL。通过加入奖惩因子,同时对精英个体采用蚁群优化算法的概率生成新的后代个体,对于普通个体,通过与随机选择的精英个体进行交叉变异操作,改进蚁群优化算法,以整个网络每次通信的能耗为优化目标选取较优的簇头节点集。为待转发簇头节点设计从可动态调节的扇形区域中选择下一跳中继节点的链路转发策略。实验结果表明,与现有协议相比,该协议在延长网络寿命、提高通信链路质量、增强网络覆盖度方面表现良好。Aiming at the situation that wireless sensor networks with large network coverage area and large number of nodes are prone to premature death of some nodes,an improved ant colony clustering routing protocol RACO-SL based on sector link stra-tegy was proposed.Reward and punishment factors were added,the probability of the ant colony optimization algorithm was used for elite individuals to generate new offspring individuals,and for ordinary individuals,the ant colony optimization algorithm was improved by cross-mutation operation with randomly selected elite individuals,and the optimal cluster node set was selected with the goal of energy consumption optimization of each communication of the entire network.A link forwarding policy was designed for the cluster head node to be forwarded by selecting the next-hop relay node from a dynamically adjustable sector area.Experimental results show that compared with the existing protocol,the protocol performs well in extending the network life,improving communication link qualities,and enhancing network coverages.

关 键 词：无线传感器网络 分簇路由协议 多跳 扇形链路策略 蚁群优化算法 簇头节点选择 能量均衡 网络覆盖度 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]