SBOA: Optimizing VM Failures and Operational Cost for Task Scheduling in Cloud-Fog Environment

In Cloud-Fog Computing (CFC) environments, virtual machine (VM) failures and high operational costs are critical challenges that hinder efficient task scheduling. To address these issues, this paper proposes the Secretary Bird Optimization Algorithm (SBOA), inspired by the bird's hunting strategies, to optimize task scheduling while minimizing VM failures and reducing operational costs. SBOA leverages adaptive search mechanisms for dynamically balancing workloads between cloud and fog nodes, ensuring high resource utilization and system reliability. Simulation results demonstrate that SBOA reduces VM failure rates by 24%, operational costs by 19.6% and enhancing fault tolerance and energy-efficient resource allocation, significantly outperforming conventional algorithms in cloud-fog environments.