Fuzzy Based Ant Colony Optimization Approach for Wireless Sensor Network

Wireless sensor networks have spread their presence to every other domain we could think of with the technological advancements in the Information Technology. The core component of the WSN are the sensor nodes, which gather the environmental information of the area in which they are deployed and forwards it to the base station for further processing. WSNs are associated with the low network lifetime problem, which restricts in achieving maximum performance. To increase the lifetime, fuzzy system has gained popularity among the systems which are associated with redundant and non-exact information and is being widely used in the optimization problems. In this paper a cluster based hierarchy approach similar to LEACH algorithm has been proposed with fuzzy inference system for the cluster head election along with the ant colony optimization, which is a swarm intelligence based technique used for the routing of data between the sensor nodes and the base station. The proposed approach has been proved to be better as compared to the LEACH algorithm and can be observed from the simulation results where the proposed approach outperforms in terms of residual energy of the system, the number of packets transmitted to the base station and the stability period of the system.