ADAPTIVE HYBRID DRAGONFLY FIREFLY (AHDF) ALGORITHM FOR OPTIMIZED CLUSTER HEAD SELECTION IN WIRELESS SENSOR NETWORKS

Abstract

Wireless Sensor Networks are everywhere around us used in variety of applications such as weather forecasting, military surveillance, health monitoring, agriculture monitoring, and smart IoTs etc. These networks are particularly employed to sense and broadcast the data from source nodes to sink node. Hence, energy consumption becomes one of the most challenging jobs here. Hierarchical clustering-based routing schemes prove to be helpful in such situations. As a result, optimized cluster head selection is essential and key task here. In this paper author has attempted to design an optimized cluster head selection scheme based on Adaptive Hybrid Dragonfly Firefly (AHDF) algorithm on the basis of node energy, corresponding distance and network load and delay parameters. The simulation and comparison results showcase the outperformance of the proposed routing scheme in terms of energy efficiency (121% and 41%), network lifetime (89% and 21%) and data throughput (31% and 23%) in comparison of existing routing schemes SEELCA [15] and CRCGA [16] respectively.