CSPBOT - boQIEKC: QoS Enhanced Integration OF Energy-Aware Clustering with Routing Protocol for WSN

Nowadays, demanding ideals in Wireless Sensor Network (WSN) research are prolonging the network lifetime and lessening the energy consumption. However, the WSN with dynamic topology communication among Sensor Nodes (SNs) is liable to various attacks. SNs with low power may create some issues between security and energy consumption. In this proposed methodology, a protected energy-efficient routing approach, namely the Combinable Stochastic Patterned Bat Optimization Technique based on Quantized Indexive Energy Knowledgeable Clustering (CSPBOT -boQIEKC), is introduced. It performs SN clustering, shortest path identification, and path maintenance. Clustering and CH election are done by the Quantized Schutz Indexive Linde Buzo Gray (QSILBG) Algorithm. Meanwhile, the Cluster Head (CH) election is done by considering distance, residual energy of the SNs, and delay. Shortest path identification is performed by Combinable Stochastic Patterned Prevosti's Bat Optimization (CSP2BO) Technique. Furthermore, the fitness of the bat is estimated based on the distance, energy, trust and link stability among SNs. In addition, the fault tolerance approach is utilized to ensure that the WSN continuously works regularly, even in the state of CH failure. The Stochastic Universal Sampling Selection (SUSS) procedure is activated to elect the best shortest path for data transmission. Finally, path maintenance is accomplished for alternative paths when link failure happens among SNs of the network. The performance of the proposed methodology is estimated on residual energy, energy consumption, packet delivery ratio, network lifetime and throughput. The proposed CSPBOT-boQIEKC technique provides an 18% improvement in energy consumption, 6% improvement in PDR, and 26% improvement in throughput than existing Taylor C-SSA, QEBSR and IoNM-BSOLyD approaches.