对具有NP完全难度的网络状态动态变化下的路由问题,提出了一种基于蚁群网络(A n tnet)的蚁群优化分布式Q oS路由算法.算法的主要特点是:(1)采用了动态更新的概率表替代传统的路由表;(2)采用了智能的初始化方法;(3)采用了一种新颖的信息...对具有NP完全难度的网络状态动态变化下的路由问题,提出了一种基于蚁群网络(A n tnet)的蚁群优化分布式Q oS路由算法.算法的主要特点是:(1)采用了动态更新的概率表替代传统的路由表;(2)采用了智能的初始化方法;(3)采用了一种新颖的信息素更新机制;(4)采用一种新的节点选择机制;(5)引入蚂蚁相遇机制.与标准的A n tN et相比,该算法具有更快的收敛速度和较好的吞吐能力.另外,算法同时考虑了满足Q oS度量和负载平衡等问题.展开更多
Improving routing algorithm performance not only leads to appreciate the quality of data transmission, but also increases the speed of data transfer. In this paper we propose a hybrid method which is a combination of ...Improving routing algorithm performance not only leads to appreciate the quality of data transmission, but also increases the speed of data transfer. In this paper we propose a hybrid method which is a combination of traffic classification by the help of colored pheromones and helping ants method in the intermediate nodes. This combination increases the convergence speed and decreases the delay and Jitter in the network. Also we compare the obtained results with two known routing algorithms that are based on the ant colony.展开更多
文摘对具有NP完全难度的网络状态动态变化下的路由问题,提出了一种基于蚁群网络(A n tnet)的蚁群优化分布式Q oS路由算法.算法的主要特点是:(1)采用了动态更新的概率表替代传统的路由表;(2)采用了智能的初始化方法;(3)采用了一种新颖的信息素更新机制;(4)采用一种新的节点选择机制;(5)引入蚂蚁相遇机制.与标准的A n tN et相比,该算法具有更快的收敛速度和较好的吞吐能力.另外,算法同时考虑了满足Q oS度量和负载平衡等问题.
文摘Improving routing algorithm performance not only leads to appreciate the quality of data transmission, but also increases the speed of data transfer. In this paper we propose a hybrid method which is a combination of traffic classification by the help of colored pheromones and helping ants method in the intermediate nodes. This combination increases the convergence speed and decreases the delay and Jitter in the network. Also we compare the obtained results with two known routing algorithms that are based on the ant colony.
