Hybrid Optimization algorithm for clustering and Routing in WSN

Wireless Sensor Network (WSN) exemplary incorporate thousands of corresponding miniature nodes, individually provisioned along discern mechanism. Thereby, the node which carry pivotal energy rein is unsubstantial where the energy doesn’t replace and conspire at one time. Accordingly, energy utilization in WSN is due to transmission of data. Clustering is a systematic approach to attain the energy efficient via data transfer in Wireless Sensor Network. So, this research intended Multi Objective - Energy based Hybrid Optimization Algorithm – (MOEHOA) is initiated to achieve procedure which is energy competent. The combination optimization algorithm is appeased of enhanced Moth Flame Algorithm (IMFO) with Firefly algorithm. Besides, this preferred technique eradicates exaggerated retransmissions and delay which consequences in improving the performances. The simulation model demonstrated that proposed MOEHOA attained greater outcome with reference to end-to-end delay (12.65 ms), residual energy (12.7725 J), normalized routing overhead (0.118949), packet delivery ratio (0.994), and throughput (1.097 Mbps) meanwhile correlated with Cluster Based Data Aggregation (CBDA) acquires smaller attainment in all the recital criterions.