A Comprehensive Analysis on Clustering and Routing Techniques in Wireless Sensor Network

Wireless Sensor Networks (WSN) is utilized as front-end communication systems in home automation, environment monitoring, industry, Internet of Things (IoT), etc. The extension of the lifetime of WSNs enhances the utilization of various applications and systems to communicate and interact efficiently. However, cluster heads (CHs) and relay nodes face the difficulties of energy balancing, nodes having limited capability for storage systems, communication, resource management and computational power which further results in corrupted nodes and data becoming vulnerable to improper access. The optimization algorithms namely Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), and Butterfly Optimization Mechanism (BOM), and Fuzzy Logic (FL)-based techniques are used for reduce the delay in CH selection and routing protocols. This research aims to research the strengths, relationships, and challenges of delay-aware clustering and routing for WSN-based approaches, thereby minimizing the EC and increasing network lifetime.