ENERGY-EFFICIENT CROSS LAYER OPTIMIZED CLUSTERING ROUTING (EECLOCR) PROTOCOL AND CHAOTIC PUFFERFISH OPTIMIZATION ALGORITHM (CPOA) FOR WIRELESS SENSOR NETWORK (WSN)

Abstract

ABSTRACT: Wireless Sensor Network (WSN) are powered by batteries that have a limited capacity, the network's quality could decline at any timesince the majority of sensor nodes. It becomes quite challenging to decrease sensor node energy consumption and increase network lifetime. Every sensor node can use the limited energy more sensibly by creating an efficient clustering routing protocol. The four main operations that make up this system are Cluster Head Election (CHE), cluster creation, data fusion, and data transfer. Routing protocols, CHE nodes are crucial for effective communication in WSN. In this paper, Energy-Efficient Cross Layer Optimized Clustering Routing (EECLOCR) protocol is presented to organize the Sensor Node (SN) into clusters. Firstly, a novel K-medoids is first introduced for cluster formation. Secondly, the Chaotic Pufferfish Optimization Algorithm (CPOA) determines the number of CH and the optimal CH to choose, and sensor nodes are paired with the nearest CH. In each iteration, the CPOA algorithm selects a group of CH to construct various cluster networks in an attempt to identify the best possible network configuration. Use the intra-cluster distance, total distance, energy consumption, and residual energy ratio is introduced to optimize the selection of CH. It is capable of minimizing transmission distance and optimizing energy efficiency. Thirdly, network overhead is dynamically minimized by using the EECLOCR protocol to find the quickest route. Proposed method produced better results when evaluating the Packet Delivery Ratio (PDR), Packet Loss Ratio (PLR), Network lifespan, Energy Consumption, and throughput than other methods.