Improved Artificial Fish Swarm Algorithm And Its Application In QoS Routing Problem

With the rapid growth of the Internet, IP service has been rapidly risen and diversified, which greatly changes the consumers'expectations to the performance, security and service of network. A variety of real-time and multimedia applications appear, and ask for higher demands for the QoS. To solve the problem of multicast routing constrained with QoS has become the key of multi-media information transmission. QoS routing problem has become a focus of the current academic research. So far, ant colony algorithm has been successfully applied in solving QoS routing problems and obtain good results. Based on the achievements of this field, this article combines artificial fish swarm algorithm, ant colony algorithm and tabu search algorithm to advance an improved algorithm, and discusses its applications in QoS routing problems. The main works in this paper are as follows: First, propose a mixed algorithm of ant colony algorithm and artificial fish algorithm. Use improved Salama randomly generated network topology algorithm, randomly generate a network topology map, then use parallel search of ant colony algorithm to find a large number of feasible paths that satisfy the constraint conditions, and finally focus on the created sets of alternative paths by using artificial fish-swarm algorithm, and seek out the optimal multicast tree through the implementation of feeding, clusters and rear-end. Second, propose a mixed algorithm of artificial fish algorithm and tabu search algorithm. Divide the region to be searched into several sub-regions and use the convergency of fish-swarm algorithm to quickly reach a sub-optimal solution in all regions, and then to seek out a second-best solution as the initial solution of tabu search algorithm, meanwhile use tabu search algorithm to find the optimal solution in all regions. And finally use bubble sort method to order the optimal solution in all regions thus find the global optimal solution. The simulation experiment shows that the two improved methods are better than common algorithms in solving QoS routing problem, in terms of speed and efficiency as well.