A hybrid optimization approach using PSO and ant colony in wireless sensor network

Abstract In the wireless sensor network, different roles has been playing like clustering, data aggregation, and transmission and routing. Above all, routing has been now in most consideration because the network’s lifetime is totally dependent upon the routing. The network’s all parameters like dead node, alive node, throughput, remaining energy etc are dependent upon the factor which is called routing. If proper path has been decided by the network then the throughput must be increased and the system’s lifetime will be more. In this paper, the whole contribution is placed towards the routing which involves in the WSN. For major concern towards the routing, the optimization has been done. The optimization made the network more stable and enhances their performance. Several optimization techniques which are present in the swarm intelligence has been taken like ant colony, particle swarm, cuckoo search, flower pollination etc. Although, such techniques have been used but their hybrid approach also increase its durability in various fields. The ACO-PSO hybrid approach has been introduced for the optimization process which will enhances the lifetime because the ACO approach is widely used for the local updates and PSO approach is used for the global updates and makes the reliable path. From simulations, we observed that the proposed approach has 6% improvement over the previous one and it is best way to find out the optimal solutions.