Energy Efficient Clustering and Routing Protocol for Internet of Things Using Optimization Algorithms

Internet of things (IOTs) are crucial in monitoring environmental conditions in remote areas, but they face significant challenges related to energy consumption, which affects network longevity and coverage. Clustering has proven effective in prolonging the life of sensor networks. FFA (Fruit Fly Algorithm) and ACO (Ant Colony Optimization) are emerging as encouraging solutions for creating clusters and establishing paths, respectively. This paper proposes a novel solution that integrates ACO for establishing paths with FFA for clustering. This method is tested in both homogeneous and heterogeneous settings using MATLAB, comparing its performance with two existing algorithms: Low Energy Adaptive Clustering Hierarchy (LEACH) and Biogeography-Based Optimization Algorithm (BOA). According to the findings, the suggested algorithm performs noticeably better than BOA and LEACH in the context of coverage area and network service period, especially in heterogeneous settings