ADAPTIVE PUFFERFISH OPTIMIZATIONALGORITHM (APOA) AND CLUSTERING TRUST ENERGY AWARE ROUTING (CTEAR) PROTOCOL FOR EH-WSN

Abstract

 Wireless Sensor Network (WSN) is critical in supporting continuous environmental monitoring to gather and transport data from the environment to a base station. Here the sensor nodes are deployed and need to be operational. WSN faces a number of difficulties because of their working conditions, resource constraints, and communication features. It reflects in enhancing security and optimizing energy to ensure network security and prolong network lifetime. Thus, Cluster Head (CH) selection in Energy Harvesting- Wireless Sensor Network (EH-WSN) is a flexible technique. In this paper, Clustering Trust Energy Aware Routing (CTEAR) is introduced with restricted energy of WSN nodes in order to increase network security.The interaction between the CH and Cluster Member (CM) serves as the foundation for CTEAR. Trust level of nodes are exponentially reduced or improved depending on their hostile behaviors with trust parameters such as reception rate, redundancy rate, energy, and signal-to-noise ratio. Data Transmission (DT) and Cluster Establishment (CE) are the major parts of clustering. During CE, Possibilistic Fuzzy C-Means (PFCM) clustering is developed for clustering in WSN. After forming a cluster, each region selects CH using the multi-criteria using the Adaptive Pufferfish Optimization Algorithm (APOA). Each CM in the cluster, DT, awakens during its allotted working hours and sends the information it has collected to the CH. Routing protocols are finally measured using metrics like Residual Energy (RE), Packet Delivery Ratio (PDR), Packet Loss Ratio (PLR), energy consumption, Network Lifetime (NL), throughput, delay, and detection rate. MATrix LABoratory R2022a (MATLABR2020a), routing protocols are simulated and their performance is compared with other secure routing methods.