Zheng, Guhan and Ni, Qiang and Navaie, Keivan and Pervaiz, Haris (2024) Semantic Communication in Satellite-borne Edge Cloud Network for Computation Offloading. IEEE Journal on Selected Areas in Communications, 42 (5). pp. 1145-1158. DOI https://doi.org/10.1109/jsac.2024.3365879
Zheng, Guhan and Ni, Qiang and Navaie, Keivan and Pervaiz, Haris (2024) Semantic Communication in Satellite-borne Edge Cloud Network for Computation Offloading. IEEE Journal on Selected Areas in Communications, 42 (5). pp. 1145-1158. DOI https://doi.org/10.1109/jsac.2024.3365879
Zheng, Guhan and Ni, Qiang and Navaie, Keivan and Pervaiz, Haris (2024) Semantic Communication in Satellite-borne Edge Cloud Network for Computation Offloading. IEEE Journal on Selected Areas in Communications, 42 (5). pp. 1145-1158. DOI https://doi.org/10.1109/jsac.2024.3365879
Abstract
The low earth orbit (LEO) satellite-borne edge cloud (SEC) and machine learning (ML) based semantic communication (SemCom) are both enabling technologies for 6G systems facilitating computation offloading. Nevertheless, integrating SemCom into the SEC networks for user computation offloading introduces semantic coder updating requirements as well as additional semantic extraction costs. Offloading user computation in SEC networks via SemCom also results in new functional challenges considering, e.g., latency, energy, and privacy. In this paper, we present a novel SemCom-assisted SEC (SemCom-SEC) framework for computation offloading of resource-limited users. We then propose an adaptive pruning-split federated learning (PSFed) method for updating the semantic coder in SemCom-SEC. We further show that the proposed method guarantees training convergence speed and accuracy. This method also improves the privacy of the semantic coder while reducing training delay and energy consumption. In the case of trained semantic coders in service, for the users processing computational tasks, the main objective is to minimise the users’ delay and energy consumption, subject to sustaining users’ privacy and fairness amongst them. This problem is then formulated as an incomplete information mixed integer nonlinear programming (MINLP) problem. A new computational task processing scheduling (CTPS) mechanism is also proposed based on the Rubinstein bargaining game. Simulation results demonstrate the proposed PSFed and game theoretical CTPS mechanism outperforms the baseline solutions reducing delay and energy consumption while enhancing users’ privacy.
Item Type: | Article |
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Uncontrolled Keywords: | Satellite-borne edge cloud; SemCom; computation offloading; delay; energy consumption; privacy |
Divisions: | Faculty of Science and Health Faculty of Science and Health > Computer Science and Electronic Engineering, School of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 15 Apr 2024 13:53 |
Last Modified: | 30 Oct 2024 21:38 |
URI: | http://repository.essex.ac.uk/id/eprint/38206 |
Available files
Filename: Semantic_Communication_in_Satellite-borne_Edge_Cloud_Network_for_Computation_Offloading.pdf