Research On QoS Multicast Routing Algorithm Based On Genetic Multi-ant Colony Algorithm

Ant colony algorithm is a new bionic swarm intelligence algorithm, by simulating group behavior of ants in nature it converges to the optimal path, with the Accumulating, volatilizing and updating pheromones, this algorithm converges to the optimal path and has a strong positive feedback, robust and global optimization ability. With the development of broadband IP technology, multicast has been used widely in a variety of multimedia services which have real-time requirements, and QoS multicast routing problem has always been the core issue of multicast technology. Ant colony algorithms have been successfully applied to the QoS multicast routing problem, but it has shortcomings such as the lack of pheromone during the early stage and the possibility of prematurity, thus, the integration of a variety of artificial intelligence algorithms concerning s evolutionary bionic has become an important way to improve the existing ant colony algorithm .Based on the research on the traditional ant colony algorithm, this paper introduces the genetic algorithm and multi-ant ideas. By taking advantage of the global convergence and the positive feedback on the basis of ant colony algorithm, we use genetic algorithm to generate the initial pheromone distribution and to overcome the shortcomings such as the lack of pheromone, We introduce Multi-ant colony behavior when the algorithm is stagnating to improve the ability of random search and to make the algorithm out of local optimal solution. Finally, we successfully apply genetic multi-ant colony algorithm to solve the QoS problem of multicast routing.The main contents of this paper can be summarized as follows:①Discusses and analyzes the research background of multicast technology, research status, working principle, classification of multicast protocols, multicast routing algorithms and features, QoS multicast routing principles as well as the current problems in QoS multicast routing.②Describes the development process, basic concepts and principles, analyzes the processes and main features of ant colony algorithm and genetic algorithm.③Based on the research and analysis of the genetic algorithm, this paper introduces the genetic algorithm and multi-ant ideas to propose a genetic multi-ant colony algorithm. The algorithm combines the rapidity and global convergence of genetic algorithm, with the randomness of the proposed multi-ant colony behavior to improve the convergence speed and global search capability. Simulation results show that the algorithm can improve the problem in solving TSP's search capability.④Based on the study concerning the application of genetic Multi-ant colony algorithm in TSP, this paper apply the algorithm into the QoS multicast routing problem. In the QoS multicast routing problem model, Ant colony algorithm is used to generate the initial pheromone distribution. This paper converges to the optimal path by taking advantage of the positive feedback, global convergence of the ant algorithm. When the algorithm is stagnating,we can overcome the current local optimum solution situation by adopting the randomness of multi ant, and finally we can converge to a lower-cost multicast tree.⑤Generate random network through simulation and testify the feasibility and effectiveness of this algorithm in the QoS multicast routing.