Research On Ad Hoc Network QOS Multicast Routing Based On Ant Colony Algorithm

Mobile Ad Hoc network (MANET) has the characteristics of Construction of the independent network, decentralization, dynamic changes in network topology, limited bandwidth and energy, etc. Ad Hoc networks, as a special form of mobile computer networks, will have been widely used in the future, which can be deployed in battle field, temporary meeting, disaster rescue and other civil or military environments.The introduction of multimedia services proposed QoS multicast routing needs for Ad Hoc network. The QoS multicast is the special multicast which should guarantee some QoS constrains such as bandwidth, delay and packet loss rate, et. So QoS multicast is the important basis of high-bandwidth and shared Internet applications, such as stream media and video. Most of existent Ad Hoc network QoS multicast routing protocols use determinate routing, which has poor adaptability to dynamic changes of network topology. More require that the multicasting routing in Ad Hoc networks to support QoS, which is challenging.Ant colony algorithm is a kind of intelligence heuristic approach that inspired from social insects in nature. Ant colony algorithms support distributed computing and multi-path, the agents are also easy to implement .So ant colony algorithms just meet the need of mobile Ad Hoc network routing.This paper first analyses the mobile Ad Hoc network, research the characteristics, trends of the mobile Ad Hoc network and multicast necessity of the present several multicast routing protocols, through deep research of the basic ant algorithm, according to the nature of Ad Hoc network. The improved ant colony algorithm is applied in the establishment and maintenance of network multicast routing process. A new Ad Hoc network QoS multicast routing protocol based on ant colony algorithm is proposed in this paper. NS-2 Simulation results show that the protocol can effectively choose the path according to link quality, create and maintain the multicast tree, thus achieving the aims of low latency,balanced flow At the same time, the algorithm adaptively adjusts the probability routing table by using the networks information of the ants collected and achieves globally optimizing, it provides a new method to improve the congestion problem and heavy overheads problem.