The Internet of Things (IoT) is expected to improve quality of life through billions of IoT devices, connected sensors, and numerous IoT applications such as Augmented Reality (AR), Virtual Reality (VR), haptic technology, and autonomous driving. Cloud computing has served as the most crucial computing infrastructure to satisfy the computing and storage requirements needed to process the massive amounts of data generated by these sensors, IoT devices, and applications. However, rapid growth in sensors and IoT applications has consequently rendered the cloud inadequate for efficient data handling. To solve this problem, computational nodes are moved from the cloud data centres closer to the data source, which results in the area of fog/ edge computing.

Fog/edge computing enables IoT applications to improve the scalability and energy efficiency of IoT systems, exploit computational node resources to analyse the collected data, and meet latency requirements. Nevertheless, a series of challenging problems need to be addressed in order to fully utilize fog/edge computing for IoT. For instance, the majority of computational nodes in fog/edge computing are battery-operated, which means that fog/edge computing tends to be unreliable. Moreover, efficiently providing computing resources to latency-sensitive IoT applications (such as AR/VR, haptic technology, intelligent manufacturing, connected autonomous driving, and others), and seamless integration of fog/edge computing with cloud computing to provide scalable services needs to be further studied.

This Special Issue aims to provide a prime venue for researchers from both academia and industry to discuss vital problems and present innovative solutions in the area of fog/edge computing for IoT. We welcome both original research and review articles.

Potential topics include but are not limited to the following:

• Fog/Edge computing architectures and protocols for AR/VR
• Resource allocation in Fog/Edge computing for IoT
• Energy management techniques in mobile AR/VR devices using Fog/Edge computing
• Low-latency, Ultra-high reliability, and Ultra-responsive network protocols for haptic communications and AR/VR
• IoT application placement and offloading in Fog/Edge computing
• Workload balancing and scheduling in Fog/Edge computing for IoT
• Green Fog/Edge computing
• Fog/Edge computing applications in connected autonomous vehicles, Industry 4.0, smart homes, and smart cities
• Modelling and performance analysis of Fog/Edge computing for IoT
• The collaboration of cloud computing and Fog/Edge computing for IoT
• Mobility management in Fog/Edge computing for IoT
• Open issues and challenges in Fog/Edge computing for IoT
• Transmission and communication strategies in Fog/Edge computing for IoT