| 注册
首页|期刊导航|计算机应用研究|基于子网融合的多智能体系统自组网连通性恢复方法

基于子网融合的多智能体系统自组网连通性恢复方法

何杏宇 余萍萍 杨桂松

计算机应用研究2024,Vol.41Issue(10):3135-3140,6.
计算机应用研究2024,Vol.41Issue(10):3135-3140,6.DOI:10.19734/j.issn.1001-3695.2024.03.0040

基于子网融合的多智能体系统自组网连通性恢复方法

Self-organized network connectivity recovery method for multi-agent system based on subnet fusion

何杏宇 1余萍萍 2杨桂松2

作者信息

  • 1. 上海理工大学光电信息与计算机工程学院,上海 200093||上海理工大学出版印刷与艺术设计学院,上海 200093
  • 2. 上海理工大学光电信息与计算机工程学院,上海 200093
  • 折叠

摘要

Abstract

It is challenging to quickly restore full connectivity in a damaged multi-agent self-organizing network while maintai-ning the residual connectivity structure.Therefore,this paper proposed a connectivity restoring method based on subnet fusion for self-organized networks in multi-agent systems.Firstly,the method designed a subnet partition algorithm based on network fault detection,to identify faulty nodes and subnet fragmentation in the system.Secondly,the method deployed a leader-follower mobility model within each subnet to maintain the residual network connectivity.Finally,the method designed a rein-forcement learning-based subnet fusion algorithm for leader election,where elected leaders periodically according to a reward function related to mobility distance and energy consumption,being responsible for guiding their followers to move for fusion between subnets.The experimental results show that this method reduces average restoration time by 11.3%and decreases en-ergy consumption by 10.58%,demonstrating its advantages in efficiency and energy usage.

关键词

多智能体系统/连通性恢复/领航-追随者/强化学习

Key words

multi-agent system/connectivity restoration/leader-follower/reinforcement learning

分类

信息技术与安全科学

引用本文复制引用

何杏宇,余萍萍,杨桂松..基于子网融合的多智能体系统自组网连通性恢复方法[J].计算机应用研究,2024,41(10):3135-3140,6.

基金项目

国家自然科学基金资助项目(61602305,61802257) (61602305,61802257)

上海市自然科学基金资助项目(18ZR1426000,19ZR1477600) (18ZR1426000,19ZR1477600)

南通市科技局社会民生计划资助项目(MS12021060) (MS12021060)

浦东新区科技发展基金产学研专项资助项目(PKX2021-D10) (PKX2021-D10)

敏捷智能计算四川省重点实验室开放式基金资助项目 ()

计算机应用研究

OA北大核心CSTPCD

1001-3695

访问量0
|
下载量0
段落导航相关论文