Fair Scheduling and Computation Co-Offloading Strategy for Industrial Applications in Fog Networks

• Published in: IEEE eTransactions on network and service management p. 1
• Main Authors: Hazra, Abhishek, Adhikari, Mainak, Kumar, Dipak, Amgoth, Tarachand
• Format: Journal Article
• Language: English
• Published: IEEE 15.11.2023
• Subjects: Delays; End-to-End Delay; Fog Computing; Industrial Applications; Industrial Internet of Things; Internet of Things; Job shop scheduling; Lyapunov Optimization; Optimization; Processor scheduling; Servers; Task analysis
• ISSN: 1932-4537
• DOI: 10.1109/TNSM.2023.3332763

Nowadays, by integrating the Industrial Internet of Things (IIoT) with fog networks, companies can efficiently manage the increasing data traffic and enhance the capabilities of sensing devices. However, control of critical IIoT applications has become difficult because of the increasing demand for technology during the Industry 4.0 revolution and the use of fog computing. To address this issue, we introduce an efficient resource provisioning strategy called Fair Scheduling and Computation Co-offloading (FSCC) for executing the maximum number of tasks within the corresponding deadline while achieving network stability. Initially, we formulate the task scheduling problem as a stochastic problem and devise a novel optimization framework by exploiting the Lyapunov optimization technique. A two-phase task offloading strategy is also proposed to efficiently offload scheduled tasks to suitable computing devices in fog networks. The proposed FSCC strategy combines devices' current state information and a collaborative fog-cloud infrastructure for controlling network parameters and utilizing available fog resources. Experimental results demonstrate that the proposed strategy improves 15-20% end-to-end delay and deadline satisfaction over existing methods.