An examination of IIoT and fog computing architectures, applications and challenges from IoT to Industry 4.0

Abstract

The rapid development of Industry 4.0 has accelerated the deployment of Industrial Internet of Things (IIoT) technologies, allowing for extensive communication between industrial infrastructure, sensors, actuators, and cyber-physical systems. However, major architectural challenges arise in terms of scalability, interoperability, latency, and security because of the enormous volume of heterogeneous data produced and the stringent real-time requirements. Fog computing, which connects edge devices and centralized cloud systems, has become a crucial intermediary layer in this environment. With an emphasis on fog computing-based industrial systems, this paper offers an organized and critical literature analysis of IIoT designs. This review is based on a systematic selection of peer-reviewed papers drawn from major scientific databases. It proposes a taxonomy of IIoT designs, categorized into cloud-centric, edge-optimized, fog computing-based, and hybrid models. To assess their performance in terms of energy efficiency, scalability, interoperability, resilience to cyber attacks, and latency management, a comparative study is carried out. The investigation identifies a number of outstanding issues, such as multi-layered security flaws, interaction with current industrial infrastructures, distributed fog computing orchestration, and large-scale deterministic real-time communication. This study offers a systematic framework to direct future improvements of scalable, secure, and energy-efficient IIoT ecosystems by synthesizing previous research and addressing specific research gaps.