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。
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.
出处
《电子科技大学学报》
EI
CAS
CSCD
北大核心
2009年第2期266-269,共4页
Journal of University of Electronic Science and Technology of China
基金
四川省科技攻关项目(07GG006-014)
关键词
蚁群算法
遗传算法
基于路由的服务质量
信息素
ant colony optimization
genetic algorithms
QoS-based routing
trail information
