计算机工程与应用 ›› 2011, Vol. 47 ›› Issue (36): 112-114.

• 网络、通信、安全 • 上一篇    下一篇

双向反馈蚁群算法在网络负载均衡问题的研究

王爱静1,郝志峰1,黄 翰2,3,李学强2   

  1. 1.广东工业大学 计算机学院,广州 510006
    2.华南理工大学 软件学院,广州 510006
    3.南京大学 计算机软件新技术国家重点实验室,南京 210093
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2011-12-21 发布日期:2011-12-21

Load balance and optimization of network resources based on two-
direction feedback ant colony algorithm

WANG Aijing1,HAO Zhifeng1,HUANG Han2,3,LI Xueqiang2   

  1. 1.School of Computer,Guangdong University of Technology,Guangzhou 510006,China
    2.School of Software Engineering,South China of Technology,Guangzhou 510006,China
    3.State Key Laboratory for Novel Software Technology,Nanjing University,Nanjing 210093,China
  • Received:1900-01-01 Revised:1900-01-01 Online:2011-12-21 Published:2011-12-21

摘要: 针对网络资源管理中的负载均衡与优化问题,提出一种双向反馈蚁群算法,用蚂蚁数量代表网络资源流量,通过蚂蚁间信息素的相互作用和动态控制来实现网络流量分担到多条可用路径。将蚁群算法扩展为双向反馈的蚁群算法,蚂蚁判断各条路径上的信息素浓度的同时,考虑可选链路的负载情况,决定选择要走路径,使得蚂蚁相对均衡地分布在可选链路上。仿真实验结果表明,双向反馈蚁群算法比原蚁群算法在缩短自适应时间,减少丢包率,提高负载均衡效率方面都具有更好的性能。

关键词: 双向反馈蚁群算法, 蚁群算法, 网络资源优化, 负载均衡

Abstract: Two-direction feedback ant-colony algorithm is presented which aims at load balance and optimization of network resources management.Through the interaction and dynamic update among the pheromone of ants which are on behalf of the network traffic,the algorithm enables network traffic to share a number of paths available.The algorithm expands the ant colony algorithm for two-direction feedback ant colony algorithm.When the ant judges every path of pheromone strength,it also considers optional link load conditions,then determines which path to choice.It makes the link has the relatively balanced distribution.The results of simulation experiment demonstrate that compared with ant colony load balance algorithm two-direction feedback ant colony algorithm has superiority in reducing time of auto adaption,lowering packet loss rate and improving efficiency of load balance.

Key words: two-direction feedback ant colony algorithm, Ant Colony Optimization(ACO), network resource optimization, load balancing