IDLOA: Prioritized Task Scheduling for Optimizing Resource Utilization in Cloud-Fog Environment

Abstract

In Cloud-Fog Computing (CFC) environment efficient task scheduling is crucial for optimizing resource utilization and system performance. This paper presents a novel approach by integrating the Improved Dingo Optimization Algorithm (IDOA) and the Lion Optimization Algorithm (LOA) into the Improved Dingo Lion Optimization Algorithm (IDLOA). Inspired by dingo and lion foraging behavior, IDLOA offers a nature-inspired optimization technique for dynamic task allocation in CFC environments. The methodology aims to minimize response time, energy usage, and overall operational costs by dynamically adapting to changing conditions. Extensive simulations and comparative analyses demonstrate that IDLOA outperforms existing algorithms, reducing response time, energy usage, and operational costs by 21%,32%, and 27%, respectively. These results highlight the significant contribution of IDLOA to optimizing CFC environments, emphasizing its potential for real-world applications requiring efficient resource utilization.