A Hybrid RF-FSO Offloading Scheme for Autonomous Industrial Internet of Things
- Resource Type
- Conference
- Authors
- Pliatsios, Dimitrios; Lagkas, Thomas; Argyriou, Vasileios; Sarigiannidis, Antonios; Margounakis, Dimitrios; Saoulidis, Theocharis; Sarigiannidis, Panagiotis
- Source
- IEEE INFOCOM 2022 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) Computer Communications Workshops (INFOCOM WKSHPS), IEEE INFOCOM 2022 - IEEE Conference on. :1-6 May, 2022
- Subject
- Communication, Networking and Broadcast Technologies
Radio frequency
Energy consumption
Monte Carlo methods
Simulation
Conferences
Transceivers
Hybrid power systems
Computation Offloading
Energy Efficiency
Free-space Optical Communications
Industrial Internet of Things
Multi-access Edge Computing
- Language
The ever increasing demand for bandwidth triggered by data-intensive applications is imposing a considerable burden on the radio-frequency (RF) spectrum. A promising solution to address the spectrum congestion problem is the adoption of free-space optical (FSO) communications. In this work, we consider a hybrid RF-FSO system that enables the task offloading process from Industrial Internet-of-Things devices to a multi-access edge computing (MEC)-enabled base station (BS). We propose a solution that minimizes the total energy consumption of the system by deciding whether the RF or FSO link will be used for the task offloading and optimally allocating the device transmission power while taking into account the task requirements in terms of delay. The proposed solution is based on a decomposition-driven algorithm that employs integer linear programming (ILP) and Lagrange dual decomposition. Finally, we carry out system-level Monte Carlo simulations to evaluate the performance of the solution. The simulation results show that the proposed solution can minimize the total energy consumption within a few iterations, while also considering the respective latency requirements.