Optimal Cluster Based Routing Technique for Wireless Sensor Networks using Hybrid Optimization Algorithm for Maximizing Life of Sensors

Wireless Sensor Network (WSN) has many sensor nodes that connect with sync nodes. The sensor node's power is a limitation. The expense and difficulty of battery charging and replacement affect sensor node life and network length. Clustering reduces the cost of internal cluster communication, thereby conserving energy. Generally, researchers seek for low energy usage via providing data to monitor the cluster's energy use. Many of them are tied to network length. The Ant Group (TAS) technique is the first notion for establishing a cluster using the OC algorithm that saves electricity. Next, we use improved myopia (IM) to find the cluster head (CH). This minimises the number of clusters and the expense of internal communications. The proposed OC-TAS-IM algorithm attempts to enhance energy efficiency. In the network. The route is also conducted using a special algorithm in the low energy adaptive cluster range (reach). It contains Network Simulator implementation and simulation experiments to test specific OC-TAS-IM algorithms (NS2). Because of optimum clustering, the OC-TAS-IM method is stable in terms of energy clustering and grid lifespan.