摘要
针对无线传感器网络能耗不均衡、网络生存期短的问题,提出一种基于改进灰狼优化的分簇路由算法.在簇构建阶段,首先采用自组织神经网络映射(SOM)对网络节点聚类分簇,然后在簇内使用改进的灰狼优化算法选择最优簇头;簇间路由阶段,综合考虑节点的剩余能量和地理位置,为簇首选择合理的下一跳;簇内通信阶段,引入轮询控制机制,进一步降低网络能耗.仿真结果表明:在不同规模的场景下,所提算法均能够均衡网络能耗、延长网络生存期、提高网络吞吐量.
In order to solve the problems of uneven energy consumption and short network lifetime in wireless sensor networks,a clustering routing algorithm based on improved grey wolf optimization is proposed.In the cluster construction phase,the self-organizing map network(SOM)clustering algorithm is used to cluster the network nodes,and then the improved grey wolf optimization algorithm is used to select the optimal cluster head in each cluster.In the inter-cluster routing stage,a reasonable next hop is selected for the cluster head by comprehensively considering the residual energy and geographical location of the nodes.In the intra-cluster communication phase,polling control mechanism is introduced to further reduce network energy consumption.Simulation results show that the proposed algorithm can balance the network energy consumption,prolong the network lifetime and improve the network throughput in different scale scenarios.
作者
侯鹏
贺之航
袁也
晋士程
HOU Peng;HE Zhi-hang;YUAN Ye;JIN Shi-cheng(School of Information Science and Engineering,Yunnan University,Kunming 650500,China;School of Civil and Traffic Engineering,Shenzhen University,Shenzhen 518060,China)
出处
《微电子学与计算机》
2021年第5期54-59,共6页
Microelectronics & Computer
基金
国家自然科学基金项目(61560092)
云南大学信息学院研究生科研创新项目(Y2000211)。
关键词
无线传感器网络
改进灰狼优化
自组织神经网络映射
聚类算法
路由协议
wireless sensor networks
improved grey wolf optimization
self-organizing map network(SOM)
clustering algorithm
routing algorithm
