摘要
针对水下无线传感器网络分簇路由协议的簇头选举不合理和能耗不均衡的问题,提出一种基于翻筋斗觅食策略的改进灰狼算法的水下低功耗分簇路由协议IGBSU(an improved Grey Wolf algorithm based on somersault foraging strategy for underwater low-power cluster routing protocols)。提出一种基于翻筋斗觅食策略的改进灰狼算法IGBSU,来解决传统灰狼算法的局部收敛与收敛速度慢的问题;同时结合网络能耗模型得出最优簇头数量;利用改进的灰狼算法进行簇头选举,在设计适应值函数时综合考虑了节点能量、距离、密度、当选簇头频数、能耗速率5种因素;在簇间路由过程中采用考虑角度因子的蚁群算法选取最优传输路径。实验结果表明,协议IGBSU能够有效减缓节点死亡速度,降低网络能耗,延长网络生命周期。
To address the issues of unreasonable cluster head election and unbalanced energy consumption in clustering routing protocols for underwater wireless sensor networks,an underwater low-power clustering routing protocol named IGBSU,based on an improved Grey Wolf Optimizer incorporating the somersault foraging strategy,was proposed.An improved grey wolf algorithm based on somersault foraging strategy was proposed to solve the problem of local convergence and slow convergence speed of the traditional grey wolf algorithm.Concurrently,the optimal number of cluster heads was derived by combining with the energy consumption model of the network.The cluster head election was performed using the improved Grey Wolf algorithm,where the fitness function was designed by comprehensively considering five factors:node energy,distance,density,frequency of being elected as cluster head,and energy consumption rate.An ant colony algorithm considering the angle factor was used to select the optimal transmission path in the inter-cluster routing process.Experimental results show that the IGBSU protocol can effectively slow down the node death rate,reduce the network energy consumption,and extend the network life cycle.
作者
刘荷鑫
王福平
韦泽斌
孙帮璇
LIU He-xin;WANG Fu-ping;WEI Ze-bin;SUN Bang-xuan(School of Electrical and Information Engineering,North Minzu University,Yinchuan 750000,China)
出处
《计算机工程与设计》
北大核心
2025年第12期3482-3489,共8页
Computer Engineering and Design
基金
北方民族大学研究生创新基金项目(YCX24346)。
关键词
水下分簇路由协议
水下传感器网络
能耗均衡
灰狼算法
翻筋斗觅食策略
蚁群算法
角度因子
underwater cluster routing protocols
underwater sensor network
energy consumption balanced
Grey Wolf algorithm
somersault foraging strategy
ant colony algorithm
angle factor
