Routing Algorithm Research On The Multi QoS Constraints Based On The Ant Colony Optimization

This paper first describes the background of the routing algorithm application, then describes the overview and principles of ant colony algorithm, application context and its advantages compared to other methods, then describes the working principle of the improved ant colony algorithm and improved methods , highlighted here improved ant colony algorithm principle and program implementation. These researches by vs2005 on the experimental results show that the ant colony algorithm using the improved network performance data after the last use of the results obtained by data analysis, statistics, complete the performance comparison.Multi-QoS constrained routing optimal path problem is a typical NP-hard problem and can not be completed in polynomial time, this type of bionic ant colony optimization heuristic algorithm best suited to address this type of problem. Ant colony algorithm has many unique advantages: a strong robustness of the parallel process of routing, ease of integration with other heuristic algorithms, positive feedback, distributed computation, and greedy heuristic. Shows the path ant colony algorithm is very suitable for solving portfolio optimization problems.However, the basic ant colony algorithm is not suitable for the actual routing situation, there are many flaws. To improve the ant colony algorithm, a variety of programs, such as ant colony system , ant system with elite strategy and Max - Min ant system is proposed, but they rarely involve QoS, and their views are fragmented. This paper presents a new solved program on the basis of ACS, focuses on the QoS constraints and avoids the excess local convergence, we handle the best routing node , add QoS constraint, make the amount of changed pheromone and the growth probability P before the change links ,ues cache to speed up the speed, improve search efficiency.We use the dynamically-generated random graph to model the network environment, and analyse the routing results, we can compare path performance by the node performance, delay jitter, packet loss rate, path length and number of iterations. The results show that the improved ant colony optimization protocol can find a better path to improve network performance.