ANTHOC - QoS: quality of service routing in mobile ad hoc networks using swarm intelligence

QoS routing has received significant attention from recent literature while developing on-demand routing algorithms in ad hoc networks due to the fact that the dynamic topology changes and geographic coverage of such algorithms poses technical challenges. Swarm intelligence couples complex behaviors that arise from simple interactions. Drawing the analogy from the ant's pheromone trail- laying-and- following behavior and its rapid convergence to a globally optimum solution, the problem-solving paradigm of the ant colony optimization (ACO) is explicated. A distributed clustering algorithm is used which does not require maintaining a cluster head. Considering the network state and the precedence of the traffic, differentiated QoS parameters are applied to a fuzzy logic controller and the routing decision varies from discarding the packets to flooding. Simulation results are presented here in comparison with other well-known routing algorithms