Fog Computing for 5G Tactile Industrial Internet of Things: QoE-Aware Resource Allocation Model

• Published in: IEEE transactions on industrial informatics Vol. 15; no. 5; pp. 3085 - 3092
• Main Authors: Aazam, Mohammad, Harras, Khaled A., Zeadally, Sherali
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01-05-2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: 5G mobile communication; Cloud computing; Communication networks; Domains; Drones; Edge computing; Fifth generation (5G); fog computing; Haptic interfaces; Haptics; Industrial applications; Industrial Internet of Things (IIoT); Internet; Internet of Things; Medical services; Middleware; Quality of experience; quality of experience (QoE); Quality of service; quality of service (QoS); Remote control; Resource allocation; Tactile Internet; Touch; User satisfaction; Wireless networks
• ISSN: 1551-3203; 1941-0050
• DOI: 10.1109/TII.2019.2902574

Fifth generation mobile communication networks are currently being deployed, thus making Tactile Internet possible. Tactile Internet is the future advancement of the current Internet of Things (IoT) vision wherein haptics, or touch and senses, can be communicated from one geographical place to another, enabling near real-time control and navigation of remote objects. Tactile Internet will have its use cases in several application domains, with the industrial sector being among the most prominent ones. With the Industrial Internet of Things (IIoT), Tactile Internet will be used in healthcare, manufacturing, mining, education, autonomous driving, etc. The acceptable delay in most of these tactile applications will be under one millisecond. Since Tactile Internet communicates haptics and gives visual feedback, quality of service (QoS) becomes an important issue. Similarly, user's satisfaction on the service quality [often measured as quality of experience (QoE)] becomes equally important. To reap the true potential of Tactile Internet, sophisticated and intelligent mechanisms are required between the end-nodes. A middleware such as fog computing can be vital in this context, since it can allocate resources based on the QoS/QoE requirements of each service. In this context, we present a QoE-aware model for dynamic resource allocation for tactile applications in IIoT. We implement the model using Java and discuss the empirical results to elaborate more on the impact of such a model for QoE-aware resource allocation that can be very important in the context of Tactile Internet, especially IIoT. We also discuss some of the most prominent use cases of Tactile IIoT.