A Novel Swarm Intelligence Based Routing Scheme for Manet using Weighted Pheromone Paths

The highly dynamic topology, limited bandwidth availability and energy constraints for mobile ad-hoc networks (MANETs) make the routing scenario in MANET a complex one. In this paper, we present a novel routing scheme in MANET based on ant colony optimization (ACO) algorithm that is probabilistic in nature and inspired by the foraging behavior of the real ants. This routing scheme takes into account the trip time along with the estimated queuing delay as the optimization criterion to select the route for packet transmission from source node to destination node, whereas, in the existing algorithms total path delay is determined from hop count and processing delay (a fixed value for all nodes) only, which is far away from reality. In the proposed algorithm, nonlinear weights for the deposited pheromone at the intermediate nodes are obtained by incorporating some aspects of queuing delay analysis while calculating the total path delay. Simulation results in terms of average end-to-end delay and packet delivery rate have been obtained to show the performance of the algorithm