Metaheuristic Energy Efficient Clustering Based Routing (Meecr) In Wsn - Iot

Energy exhaustion and economical energy use are the main problems in Wireless Sensor’s Network (WSN). Clustering based on the Routing (CR) is a solution in the WSN. Replacing and recharging nodes is nearly impossible of a Cluster Head (CH) and a Main Cluster Head (MCH) in CR. An energy-efficiency in the network is improper CH selection which rapidly erodes a network battery. Nondeterministic Polynomial Time (NP) is a hard problem that it easily fits into CH selection issue. This study includes the effective use of limited energy resources of nodes in the WSN is used to increasing in the network of whole lifetime. Metaheuristic Energy Efficient Clustering Based the Routing of method (MEECR) consists of multiple stages like K-Means clustering, CH and MCH election based on Residual Energy (RE) and Relative Position (RP), communication considering the energy use model, and the best route selection. For WSN-IoT energy management and network lifetime extension, the Powell Cat Swarm Optimization Algorithm-Cluster Head Selection (PCSOA-CHS) is presented as a potential solution. The ideal CH and MCH selection is modeled after the habits of cats by PCSOA-CHS. Determined by defining a Mixture Ratio (MR), it primarily comprises of two modules: Tracing and Seeking. Moreover accordingly to the particular results, it efficiently uses the energy resources and reduces traffic overhead. MEECR performs better than Energy’s Efficient Clustering’s Algorithm (EECA), Energy Efficient Centroid-based Routing Protocol (EECRP), and Energy’s Degree Distance Unequal Clustering Algorithm (EDDUCA).