Energy-Harvesting-Heuristic Clustering Algorithm for Distributed IoT Networks
M Velvizhi, Djagadeesan Saraswady · 2024
There are several differences in how various devices function in the complex structure of the Internet of Things (IoT), in along with complicated connections and energy limitations. Traditional scheduling modelling methods require to add a lot of constraints in order to describe the importance and limitation relationship. The objective of the present research is to use an energy-aware clustering technique to reduce energy usage in homogeneous IoT devices. By applying the Enhanced PSO optimization technique in the IoT environment for considering energy loss, the Heuristic Clustering algorithm discovers the device's idle time and optimizes the device scheduling energy consumption model to reduce the overall energy consumption of the task scheduling. This technique has the advantages of high precision and energy saving. which, when compared to current routing algorithms, significantly improves energy efficiency while addressing the QoS needs of scattered IoT networks.