Dynamic load balancing in IoT-enabled WSNs using fuzzy logic-based control

Abstract

The rapid expansion of Internet of Things (IoT) applications and the increasing complexity of Wireless Sensor Networks (WSNs) have created a critical need for efficient load balancing strategies. This paper proposes a dynamic load balancing approach for IoT-enabled WSNs using a fuzzy logic-based control mechanism. The proposed method aims to optimize energy consumption, reduce latency, and enhance network lifetime by intelligently distributing the workload among sensor nodes. The fuzzy logic controller takes into account various parameters, such as energy levels, communication distances, and node density, to make adaptive load balancing decisions. The control mechanism allocates tasks to the most suitable nodes, ensuring efficient utilization of resources and preventing overloading of individual nodes. Simulations are conducted in diverse network scenarios to validate the performance of the proposed approach. Results demonstrate significant improvements in energy efficiency, latency reduction, and overall network lifetime compared to traditional load balancing techniques. The fuzzy logic-based control mechanism proves to be a promising solution for addressing the dynamic and resource-constrained nature of IoT-enabled WSNs, paving the way for more robust and resilient networks in various IoT applications.