节点文献

ACOGA算法的多媒体网络QoS路由实现

Realization to Multimedia Network QoS Routing Based on ACOGA

  • 推荐 CAJ下载
  • PDF下载
  • 不支持迅雷等下载工具,请取消加速工具后下载。

【作者】 崔梦天钟勇赵海军

【Author】 CUI Meng-tian1,3, ZHONG Yong1, and ZHAO Hai-jun2 (1. Chengdu Institute of Computer Applications, Chinese Academy of Science Chengdu 610041; 2. School of Computer Science, China-West Normal University Nanchong Sichuan 637002; 3. Department of Computer Science, Sichuan Post and Communication College Chengdu 610067)

【机构】 中国科学院成都计算机应用研究所四川邮电职业技术学院计算机科学系西华师范大学计算机学院

【摘要】 针对传统的路由算法收敛速度慢且容易产生拥塞和路由振荡问题,提出了基于蚁群算法(ACO)和遗传算法(GAs)来实现动态QoS路由的新算法。分析了基本的ACO的正反馈性、协同性、并行性和鲁棒性等优点,同时利用GAs很强的自适应性和种群优化技术,通过对ACO算法使用遗传算法的交叉、变异达到对信息素进行调整,来自适应地调整路径选择概率的确定策略和信息量更新策略,从而扩大搜索范围。计算和仿真结果表明,该方法具有更好的路由收敛速度和稳定性,能更有效地解决拥塞现象和路由振荡问题。

【Abstract】 To solve the problem of low convergence speed and congestion and oscillation in conventional routing algorithms, a novel method of dynamic routing algorithm for multimedia network is proposed based on ant colony optimization (ACO) algorithm and genetic algorithms (GAs). The essential advantages of ACO including cooperation, positive feedback, and distributed nature and the disadvantages of low convergence speed are discussed. By considering the high adaptability of GAs, the cross operation and mutation of genetic algorithms are introduced into the ACO to improve its searching ability and to dynamically adjust the influence of each ant for the trail information updating and the selected probabilities of the paths. The algorithm is also well suited for dynamic networks and can make the selected paths shortest, miss the traffic jams and keep the balance of networks load distribution.

【基金】 四川省科技攻关项目(07GG006-014)
  • 【文献出处】 电子科技大学学报 ,Journal of University of Electronic Science and Technology of China , 编辑部邮箱 ,2009年02期
  • 【分类号】TN919.8
  • 【被引频次】9
  • 【下载频次】110
节点文献中: 

本文链接的文献网络图示:

本文的引文网络