Optimising Internet of Things (IoT) Performance Through Cloud, Fog and Edge Computing Architecture

Abstract

The Internet of Things (IoT) revolutionises communication systems and enables transformative applications across diverse domains. However, existing reviews often focus on integrating IoT with only one or two computing paradigms—cloud, fog, or edge computing—overlooking the holistic synergy of these architectures. This review bridges that gap by providing a comprehensive analysis of IoT integration with all three paradigms, emphasising their collective potential to address the challenges of scalability, latency, and computational efficiency. The findings highlight that cloud computing ensures scalable storage and processing but struggles with latency-sensitive IoT applications. Fog computing reduces latency by processing data near the network edge, achieving up to a 40% improvement in response times for real-time applications. Edge computing complements this by ensuring immediate data handling, reducing transmission delays by approximately 30% compared to cloud-centric models. Despite these advances, challenges persist, including high energy consumption, security vulnerabilities, and the complexity of managing dynamic workflows across architectures. This review provides actionable recommendations for future research, including the development of energy-efficient algorithms, robust security protocols, and adaptive frameworks for seamless integration. These directions are vital for advancing IoT as an indispensable component of the future Internet, fostering smarter and more connected systems across industries.