Swarm intelligence techniques and their applications in fog/edge computing: an in-depth review

Abstract Recent advances in the Internet of Things (IoT) have connected diverse devices that often have limited resources and processing power. Artificial intelligence (AI) applications in fog and edge computing are greatly enhanced by Swarm Intelligence (SI) techniques. These SI methods improve resource allocation, task scheduling, and load balancing, making distributed systems more efficient and responsive to changing conditions. This paper systematically reviews 91 studies (2019–2023) on SI applications in fog/edge environments. We compare fog, edge, and cloud computing paradigms and analyze SI-based approaches using case studies, performance metrics, and evaluation tools. This review identifies key advantages and limitations of current SI-based approaches and highlights open issues and future research directions to enhance distributed computing systems. These insights aim to guide the development of more efficient and responsive AI-driven resource management strategies in fog/edge environments.