A OoS Multicast Routing Problem Based On Cloud Theory-based Ant Colony Algorithm

With the high-speed development of information age, the network is fullyintegrated into the people’s daily life. People are trying to adapt to this kind of lifestyle, and looking for more comfortable experience at the same time. QoS as a kind ofmeasure arises at the historic moment. So, how to seek to use the minimum cost onthe basis of QoS to obtain maximum network resources has become an importantdirection of network research. This paper improves the efficiency of the algorithm bymeans of using cloud model based on the analysis of the ant colony algorithm whichhas some defect including choosing of rout too long, the global convergence too lowand easily falling into the local optimal.This paper uses the QoS multicast routing model to simulate, and narrate itsrelative knowledge in the middle part, which includes the knowledge of QoS, QoSconstraints, and the current situation of QoS algorithm. The paper uses Wireless routerto construct the mathematical model, and combines ant colony algorithm and cloudmodel to optimize the expense of network. So we can conclude that the algorithm isfeasible in theory which throws the final data validation.Since the positive feedback mechanism of ant colony, the searching time of thisalgorithm is too long. This paper improves the pheromone volatilization strategy,which uses cloud model to adapt dynamic planning, and dynamically adjusts the localpheromone updating strategy. At the same time, it uses the latest worst or bestupdate rules of path in overall pheromone update strategy, to improve the rate ofconvergence of the algorithm, and it also improves the global convergence of thealgorithm. The simulation results show that CACA is effective to deal with themulticast routing problem. At the same time, CACA is greatly improved inconvergence and convergence speed comparing to the traditional QoS multicastrouting algorithm, and the price tree is also optimized.