摘要
针对无线传感器网络分簇路由协议的簇首选取不合理,造成网络负载不均和生命周期缩短的问题,提出了一种基于改进蝴蝶优化算法IBOA的簇首选取算法CIBOA。首先,基于蝴蝶优化算法BOA进行改进,引入Circle混沌映射和非线性动态收敛因子来控制参数值,提高了蝴蝶优化算法的寻优速度、收敛精度,使搜索能力更强。在簇首选取过程中,根据剩余能量、节点基站间的距离和邻居节点平均间距设计了新的适应度函数,使用改进蝴蝶优化算法IBOA改进簇首选取随机的问题,综合择出更优簇首节点。仿真测试结果表明,基于改进蝴蝶优化算法的簇首选取算法CIBOA能够综合考虑节点能量和距离等因素,减少整体网络运行时间。
Aiming at the problem that the cluster head selection of clustering routing protocol in wireless sensor networks is unreasonable,resulting in uneven network load and shortened network life cycle,a cluster head selection algorithm CIBOA based on improved butterfly optimization algorithm IBOA is proposed.Firstly,based on the butterfly optimization algorithm BOA,the Circle chaotic map and nonlinear dynamic convergence factor are introduced to control the parameter,which improves the search speed and convergence accuracy of butterfly optimization algorithm,and makes the search ability stronger..In the process of cluster head selection,a new fitness function is built on the basis of the residual energy,distance among the nodes and BS and average distance between neighbor nodes.The IBOA is used for improving the random problem of cluster head selection and comprehensively select better cluster heads.Simulation results show that the cluster head selection algorithm CIBOA based on the improved butterfly optimization algorithm can comprehensively consider the factors such as node energy and distance and prolong the network lifetime.
作者
杨诗雨
赵冰
彭月
YANG Shiyu;ZHAO Bing;PENG Yue(School of Electronic Engineering,Heilongjiang University,Harbin 150080,China)
出处
《计算机科学》
CSCD
北大核心
2023年第S01期662-666,共5页
Computer Science
基金
国家自然科学基金(61801173)。
关键词
无线传感器网络
蝴蝶优化算法
簇首
混沌序列
收敛因子
Wireless sensor network
Butterfly optimization algorithm
Cluster head
Chaotic sequence
Convergent factor
