Research On QOS Routing Based On Ant Colony Optimization

Quality of Service Routing(QoSR) is a routing mechanism based on network resources available and user’s request,which is a dynamic routing protocol. QoSR’s goal is to find a feasible path that meets their QoS’s requirement for each user’s request,and to reduce the possibility of network congestion,balance network load and improve the utilization of network resources.It will ensure that the network can accept more QoS’s request.Dorigo.M found the heuristic algorithm- Ant colony algorithm when he studied ant’s forging behavior in the nature. In the process of looking for food ,ants release a volatile chemical substance–pheromone.By the mean of pheromone,ants can find the shortest path from the nest to the food source.It has many charactetistics,such as positive feedack, the essence of parallelism, a short computation time and robustness and so on.This paper analysises the a QoS unicast model,studies the ant algorithm detailly and its application status on QoS routing. This paper propsed a a multipath routing algorithm based on improves Ant Colony Algorithm (MP_ANT).To reduce the likehihood of congestion,this paper improves ant algorithm’s heuristic strategy,that the utilization ratio of router’s buffer queue is added into the criterion of selection;in order to achieve network load balance,MP_ANT selects more than one better pathes to replace the optimal path, and then uses the weighted round-robin scheduling algorithm to partition flow according to the actual situation of every path.Simulation experiments show the algorithm can achieve network loading balance,reduce the likelihood of congestion,and impove the utilization of network resources.This paper also analysises the multicast routing model, studies multicast routing’s classification explicitly and proposed a new multicast routing algorithm(SACA). In view of the deficit that ACO may lead to local optimum,SACA introduces Simulated Annealing algorithm. Simulation result shows SACA can meet multicast requirement with multiple QoS constraints,impove the ability to whole optimization.