BOA: Optimizing Energy Usage in Cloud-Fog Environment Using Meta-Heuristic Scheduling Algorithm

Optimizing energy consumption in Cloud-Fog Computing (CFC) environments is essential for enhancing efficiency and sustainability. In this paper we propose a Meta-Heuristic (MH) scheduling algorithm based on the Butterfly Optimization Algorithm (BOA) to effectively manage resource allocation and Task Scheduling (TS) between CFC. The proposed approach aims to minimize energy consumption, while improving throughput and optimizing resource utilization. Through simulation results, the BOA-based algorithm demonstrates a reduction in energy consumption by 15.6%, an increase in throughput by 18.4%, and an enhancement in resource utilization by 20.8%, compared to existing scheduling algorithms. These improvements make the BOA a promising solution for energy-efficient and performance-enhancing task scheduling in cloud-fog environments, contributing to more sustainable and responsive systems for processing large-scale, distributed workloads.