吉林大学学报(理学版) ›› 2025, Vol. 63 ›› Issue (4): 1157-1163.

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基于蚁群算法的多跳无线网络非均匀节点部署算法

蒋成   

  1. 湖北工程学院 计算机与信息科学学院, 湖北 孝感 432000
  • 收稿日期:2024-03-12 出版日期:2025-07-26 发布日期:2025-07-26
  • 通讯作者: 蒋成 E-mail:xabrejiang49@126.com

Non-uniform Node Deployment Algorithm for Multi Hop Wireless Networks Based on Ant Colony Algorithm

JIANG Cheng   

  1. School of Computer and Information Science, Hubei Engineering University, Xiaogan 432000, Hubei Province, China
  • Received:2024-03-12 Online:2025-07-26 Published:2025-07-26

摘要: 针对多跳无线网络中节点分布不均匀导致网络覆盖范围不全面, 不均匀节点的位置和密度增大部署的复杂性, 最优节点搜索易陷入局部最优解的问题, 提出一种基于蚁群算法的多跳无线网络非均匀节点部署算法. 首先, 获取最小化加权距离决策变量, 降低Sink节点到各传感器间的传输距离; 其次, 计算节点消耗的能量, 最小化节点网络损耗, 构建节点部署优化模型, 引入折中规划方法将多目标模型进行单目标化处理; 最后, 引入蚁群算法对模型求解, 能有效遍历潜在解空间, 快速找到较优的部署方案. 实验结果表明, 该算法的网络覆盖率为97%, 能量消耗最高仅为1.56×10-7 J, 能有效降低网络能量消耗, 生存周期达1 500轮, 可获取最佳节点部署方案.

关键词: 蚁群算法, 多跳无线网络, 非均匀节点, 节点部署

Abstract: Aiming at the problem that uneven distribution of nodes led to  incomplete network coverage, the uneven position and density of nodes increased the complexity of deployment, and the search for the optimal node was prone to getting stuck in local optimal solutions in a multi hop wireless network, the author proposed  a non-uniform node deployment algorithm for  multi hop wireless network based on ant colony algorithm. Firstly, the author obtained the minimum weighted distance decision variable to reduce the transmission distance between Sink nodes and various sensors. Secondly, the author calculated the energy consumption of nodes, minimized node network loss, constructed a node deployment optimization model, and introduced compromise planning method to expand the multi-objective model into a single objective processing. Finally, the author introduced ant colony algorithm to solve the model, which could effectively traverse the potential solution space and quickly find the optimal deployment plan. The experimental results show that the  network coverage of proposed algorithm is 97%, with a maximum energy consumption of only 1.56×10-7 J, which can effectively reduce network energy consumption. The survival cycle can reach up to 1 500 rounds, and the optimal node deployment plan can be obtained.

Key words: ant colony algorithm, multi hop wireless network, non-uniform node, node deployment

中图分类号: 

  • TP391