Ant Colony Routing Algorithm Based On Related Nodes For Ad Hoc Networks

Ad Hoc is a kind of self-organizing network that is multi-hops, equal nodes and wireless without any support of infrastructure. Nodes in Ad Hoc can move in and out freely. Therefore, the topology of Ad Hoc networks will be changed frequently. There is not a route which can keep a long time to communicate during the network life cycle. So routing has been highly concerned about in Ad Hoc networks.Recent years, people are discussing to use intelligent algorithm in Ad Hoc. Ant colony optimization (ACO) algorithm is a typical one. First, application of ACO algorithm in Ad Hoc has been studied. On this basis, considering the slow convergent rate of ACO in early routing, an improved scheme has been proposed, that is ant colony optimization based related nodes (RACO). When the forward ants (finding message), which were sending by source node, are looking for destination node, if a related node of destination node is found, backward ants will be generated and back. Pheromones will be left on its back way. At the same time, forward ants will continue to find the destination node or higher related level nodes of destination node.Second, study of ACO in multicast routing has been extended. Because different from traditional networks, multicast is the most appropriate for Ad Hoc. However, multicast is a NP complete problem. Conventional way is hard to be fit for frequently changing of topology of Ad Hoc. In this paper, an improved AOC scheme has been proposed, that is converse ant colony optimization algorithm in multicast routing (CACO), after studying the characteristics of multicast routing and ACO algorithm in RACO. Some backward ants will be copied to find the routing from the contrary direction when a forward ant reaches a destination node. After that the forward ant will continue to find other multicast destinations with the same operation. With this change, the convergent rate of finding multi-objective in multicast can be enhanced.Lastly, the simulation of above algorithms has been carried out. The results show that RACO can be easy to fit for frequent change of topology in Ad Hoc network. There is a better convergent rate of RACO than that of ACO in initial stage. And CACO can improve the convergent rate of finding multi-objective in multicast. Overall computation time of CACO is less than that of ACO. The average delay of end to end is better in the two algorithms than ACO. The throughput and delivery rate of RACO is better than ACO.