Genetically optimized ACO inspired PSO algorithm for DTNs

Routing is a critical issue in the Delay Tolerant Network as finding the most optimized path, with minimum loss of data and in the shortest span of time is a challenge. Various researchers have proposed different strategies for detection of the effective and efficient path.In this paper we apply a meta-heuristic method of ant colony optimization (ACO) to propose a routing mechanism for Delay Tolerant Networks to find the optimized path with maximum throughput. Modifications have been carried out in ACO to incorporate characteristics of another meta-heuristic technique known as particle swarm optimization for building up effective routing scheme. Experiments on simulated networks using agent-based modeling tool named NetLogo shows that our technique performed better as compared to the original ACO. Here the throughput has been specially taken as the performance factor of the network.