Further Investigation of Improved Antnet Routing Algorithm with Multiple Colonies

Antnet is a software agent based routing algorithm that is influenced by the unsophisticated and individual ants emergent behaviour. In real life, ants deposit some kind of chemical substance to mark the path that they used. Then on their way back they choose the path with the most pheromones which becomes the shortest path. Ants (nothing but software agents) in antnet are used to collect traffic information and to update the probabilistic distance vector routing table entries. Modified antnet algorithm improves the throughput and average delay by detecting and dropping packets routed through the non-optimal routes. In the original antnet algorithm the only feedback provided to the system by the software agents is the trip time observed on their way to source to destination. Then this feedback signal is reinforced by updating the related probability entry in the distance vector table. Due to the probabilistic routing tables used, when a network reaches to its equilibrium state stagnation problem occurs. Link usage information is used as the second feedback to the system in order to prevent stagnation problem. For every link the usage information is held at every node based on a predefined time window. Routing table entries then reinforced based on the calculated evaporation information based on the link usage statistics. In addition antnet with multiple ant colonies has been applied to packet switched networks. Here based on our previous work improved antnet, two variations of antnet employing evaporation and antnet with multiple ant colonies has been tested and compared for two different network configurations for three different network loads. Simulation results show that average delay experienced by data packets is reduced significantly after the improvements under non-uniform traffic model. However, there was no performance gain on the uniform traffic models