北京邮电大学学报

  • EI核心期刊

北京邮电大学学报 ›› 2023, Vol. 46 ›› Issue (6): 83-0.

• 论文 • 上一篇    下一篇

一种基于改进遗传算法的分簇路由算法

焦万果,丁富贵,石剑恒   

  1. 南京林业大学
  • 收稿日期:2022-08-28 修回日期:2023-02-09 出版日期:2023-12-28 发布日期:2023-12-29
  • 通讯作者: 焦万果 E-mail:wgjiao@njfu.edu.cn

A Clustering Routing Algorithm Based on Improved Genetic Algorithm

  • Received:2022-08-28 Revised:2023-02-09 Online:2023-12-28 Published:2023-12-29

摘要: 针对现有传感器网络分簇算法的不足,提出了一种基于改进遗传算法的分簇路由算法。首先,提出了一种基于和声算法和自适应优化的改进遗传算法,以解决传统遗传算法收敛慢和局部收敛的问题;然后,利用网络能耗模型与节点分布模型推导出最佳的簇头数量;最后,利用改进遗传算法选出最优的簇头,在设计适应度函数时,考虑了节点的能量、距基站距离和邻居节点密度等因素。为了均衡和降低能耗,定义入簇选择函数与中继代价函数时,考虑能量和位置因子的影响。仿真实验结果表明,所提算法可实现负载均衡并有效降低网络能耗。

关键词: 分簇路由算法, 自适应分簇, 遗传算法, 传感器网络

Abstract: To overcome the deficiency of existing clustering algorithms of wireless sensor networks, a clustering routing algorithm based on improved genetic algorithm is proposed. First, to accelerate convergence and avoid local convergence of traditional genetic algorithm, an improved genetic algorithm based on harmony algorithm and adaptive optimization method is proposed. Then, the optimal number of cluster heads is derived using the network energy consumption model and node distribution model. Finally, the optimal cluster heads are selected using improved genetic algorithm. The energy of the node, the distance from the sink, the density of neighbor nodes and other factors are considered during the design of the fitness function. In order to balance and reduce energy consumption, the energy and location factors are considered when defining the clustering selection function and relay cost function. Simulation results show that the proposed algorithm can realize load balancing and  reduce network energy consumption effectively.

Key words: clustering routing algorithm, self-adaptive clustering, genetic algorithm, sensor network

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