Systematic Literature Review on Bio Inspired Algorithms in Cloud Fog Computing

With the dynamic nature of modern computing landscapes, cloud and fog computing systems have become integral in processing and delivering services. In response to the challenges posed by these dynamic and distributed systems, bio-inspired algorithms, such as GA, PSO and ACO have emerged as promising tools for optimizing resource allocation, load balancing, energy efficiency, and various other aspects of cloud-fog computing. This review provides a comprehensive overview of the existing research, analyzing the application, strengths, and limitations of bio-inspired algorithms in these environments. It categorizes and discusses their use across resource provisioning, task scheduling, fault tolerance, security, and energy management, shedding light on their adaptability and potential to enhance system performance. By pinpointing areas where further research is needed and providing foresight into upcoming directions, this review emerges as a valuable reference for researchers, practitioners, and decision-makers. It furnishes a fundamental comprehension of how bio-inspired algorithms contribute to enhancing the efficiency and performance of cloud-fog systems in our interconnected world.