A Swarm Intelligence Based Data Aggregation Protocol for Improvement of Network Performance in Wireless Sensor Networks Clustering

Abstract

Wireless sensor networks consist of small sensor nodes of non-rechargeable battery and deployed in distant, unfriendly areas where it is infeasible to replace the battery of those nodes. Due to its limited capability of the energy, the energy efficient routing protocols are required to maximize the lifetime of wireless sensor networks. In recent years Clustering based routing protocols are proved to be best for Heterogeneous Wireless sensor networks. In this paper an efficient protocol is proposed using Glow worm swarm optimization (GSO) for heterogeneous networks. In the proposed protocol the Cluster Head is elected by a weighted probability based on the ratio between residual energy of each node, average energy of the network and distance of the node from sink node or base station. A sensor node uses single hop communication technique to inter cluster communication and Cluster heads uses Multi hop communication with the sink nodes or base station. Then data aggregation happens using the genetic algorithm to find the optimal path for efficient data transmission by reducing the communication overhead. Finally, based on the fitness of the Symbiotic Organism Search (SOS) Optimization optimal path is selected for data transmission. This protocol can improve the performance of the network energy consumption, signal strength and prolong the lifetime of Heterogeneous Wireless sensor networks as compared to other clustering protocols is shown in the simulation results.