Research On Aggregated Multicast Based On Ant Colony Optimization And MPLS Protocol

With the size of network becoming larger and people's requirements for on line transactions, a great amount of applications with large scale of multi-users multicast occur. In traditional multicast, messages between group members are transmitted through a multicast tree that can cover the group. And it requires nodes on multicast trees to maintain all groups'states. When forwarding messages, data packages are copied at every node on the tree, and are forwarded only once at every branch link. The advantage of this multicast mechanism is that the amount of copied data in the whole internet can be controlled in a small range, which can improve forwarding efficient and reduce bandwidth waste to alleviate network congestion. However, with the number of multicast groups becoming bigger, forwarding states needed to be maintained get more and increase in linear scale.If the routers need to store a large number of forwarding states, especially in backbone network where the concurrent multicast group sessions are very many, it will cause the router to require very large memory. At the same time, the process of looking up forwarding address and forwarding data packages needs to be done for each packet will therefore become very slow. Thus, when there is a large-scale multicast data forwarding in network, for the multicast groups, management will consume a large amount of resources (such as memory for maintaining multicast groups'states information) and control overhead (such as the creation and maintenance of the multicast tree Overhead). So, the problem of multicast forwarding states has affected network's performance seriously, and inhibits the re-expansion of multicast groups. This has been an important bottleneck that constraints to the development of multicast technology.In order to solve the above problem, we propose two solutions against the weaknesses of traditional multicast to settle the problem of aggregated multicast. They are Aggregated multicast algorithm based on Ant Colony Optimization and Aggregated multicast protocol based on MPLS. The following describes each of the two algorithms.1. Aggregated multicast algorithm based on Ant Colony Optimization. This algorithm is proposed for best global solution that is hard to get in traditional aggregated multicast algorithm. In this algorithm, the problem of trees' selection is converted properly. And based on the collective positive feedback effect of self-organizing and distributed collaboration in ant colony optimization algorithm, the solution required keep on moving closer to the global optimal solution. Experimental results show that this algorithm can get better solution in a short time compared with other algorithms.2. Aggregated multicast protocol. In this part, the statement is still in the highlight of algorithm about trees'selection in aggregated multicast, which we describle in detail. In addition, we also give the method of the generation of candidate trees and group-tree matching. Finally, how to manage trees efficiently is stated too. The algorithm of aggregated multicast in this protocol is to use key nodes to establish aggregated trees. In this way, the comsumption of resources in network is reduced and the forwarding efficiency is improved greatly.