Abstract
The deployment of fog computing resources in industrial internet of things (IIoT) is essential to support time-sensitive applications. To utilize resources efficiently, a brand-new request dispatcher is required to sit between the IIoT devices and the pool of fog resources. The need for such a dispatcher stems from the challenges specific to these systems. Firstly, fog-enabled IIoT systems are highly dynamic and distributed. Second, fog nodes are typically power and resource limited. Finally, many IIoT applications feature critical time-sensitivity, referred to as timeliness, and cannot tolerate response delay beyond a specific threshold. This paper proposes an efficient dispatching algorithm to minimize energy consumption and deadline misses while keeping the system stability at a satisfactory level. We leverage Lyapunov Optimization technique to tackle the problem and handle the system dynamics. We perform extensive simulations to verify the effectiveness of the proposed method and provide sensitivity, scalability and model parameter analysis. The simulation results prove the superiority of the proposed method over the state-of-the-art method up to 22% and 10% in terms of average deadline misses and energy consumption, respectively. Further, we perform practical experiments to prove the validity of the proposed method in a real testbed.
Original language | English |
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Pages (from-to) | 80-94 |
Number of pages | 14 |
Journal | IEEE Transactions on Services Computing |
Volume | 16 |
Issue number | 1 |
DOIs | |
Publication status | Published - 1 Jan 2023 |
Keywords
- Dispatching
- Edge Computing
- Energy consumption
- Fog Computing
- Heuristic algorithms
- Industrial Internet of Things
- Industry 40
- Lyapunov Optimization Technique
- Resource management
- Stability
- Stability analysis
- Task analysis
- Timeliness