A Robust Netrosophic Clustering Based Raven Routing Optimization to Alleviate Void Hole and Energy Depletion in IoT WSN

Abstract

Wireless Sensor Networks (WSNs) find extensive utilisation in diverse domains, including but not limited to environmental monitoring, industrial control, and healthcare. Wireless Sensor Networks (WSNs) have a crucial function in gathering and relaying information from sensor nodes to a central node or sink in various applications. Wireless Sensor Networks (WSNs) encounter various obstacles that can have a significant impact on their performance and lifespan. These challenges include but are not limited to limited battery life, void holes, and energy depletion.

Several routing algorithms have been suggested in scholarly works to tackle these concerns, such as clustering-based routing, data-centric routing, and location-based routing. Nonetheless, a majority of these algorithms possess constraints and may not be appropriate for every situation.

The present study introduces a methodology called Rncrro (Robust Netrosophic Clustering Based Raven Routing Optimisation) that aims to mitigate the issues of void holes and energy depletion in Wireless Sensor Networks (WSNs). The proposed approach utilises Netrosophic Clustering and Raven Optimisation algorithms in tandem to enhance the efficacy and resilience of the routing mechanism.

The significance of this study is rooted in its capacity to surmount the constraints of current routing algorithms and furnish a superior and dependable resolution for Wireless Sensor Networks (WSNs). The proposed methodology has the potential to enhance the performance and longevity of Wireless Sensor Networks (WSNs) by mitigating void holes and energy depletion. This, in turn, can result in more efficient and dependable data collection and transmission across diverse applications.