摘要
随着网络日趋复杂,求解实际的网络路由问题成为了一个NP-难问题。蚁群优化算法作为一种启发式算法近年来被广泛的用于求解复杂的NP-难问题,在对蚁群优化算法进行研究的基础上,给出了基于蚁群优化的网络路由算法—AntNet算法的原理及其NS仿真。仿真结果表明,该算法很好地利用了蚁群算法的正反馈性,能依概率随机且有效选择下一个节点,从而使网络流量按路径费用好坏,分散在多条可能的路径中,达到平衡流量、减小拥塞现象出现的目的。
As the network becoming more complicated, solving the real network routing problem becomes a NP-hard problem. Ant colony optimization algorithm as one of the heuristic algorithm in recent years is used for solving the complicated NP-hard problem. Based on the research of ant colony optimization algorithm, a simulation of AntNet is provided, which is a network routing algorithm based on ACO, on network simulator NS--2. The simulation results shows that the AntNet algorithm has well utilized positive feedback of ACO and can effectively choose the next node in accordance with probability, thus enable the network flow disperse in many possible routes, which achieves the goal of the balanced flow and reduces the congestion.
出处
《计算机与数字工程》
2010年第1期6-8,110,共4页
Computer & Digital Engineering
基金
中国博士后基金项目(编号:20080431384)资助
