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Hsieh, Cheng-Ying, Ren, Yi 
ORCID: https://orcid.org/0000-0001-7423-6719 and Chen, Jyh-Cheng
(2023)
Edge-cloud offloading: Knapsack potential game in 5G multi-access edge computing.
IEEE Transactions on Wireless Communications, 22 (11).
pp. 7158-7171.
ISSN 1536-1276
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Abstract
In 5G, multi-access edge computing enables the applications to be offloaded to near-end edge servers for faster response. According to the 3GPP standards, users in 5G are separated into many types, e.g., vehicles, AR/VR, IoT devices, etc. Specifically, the high-priority traffic can preempt edge resources to guarantee the service quality. However, even if a traffic is transmitted with low priority, its latency requirement in 5G is much lower than that in 4G. Too strict latency requirement and priority-based service make resource configuration difficult on the edge side. Therefore, we propose the edge-cloud offloading mechanism, in which each edge server can offload tasks to back-end cloud server to ensure service quality of both high- and low-priority traffic. In this paper, we establish a priority-based queuing system to model the edge-cloud offloading behaviors. Based on the formulation of our system model, we propose Knapsack Potential Game (KPG) to derive an optimal offloading ratio for each edge server to balance the cost-effectiveness of the overall system. We demonstrate that KPG has low computational complexity and outperforms two baseline algorithms. The results indicate that KPG’s performance is optimal and provides a theoretical guideline to operators while designing their edge-cloud offloading strategies without large-scale implementation.
| Item Type: | Article |
|---|---|
| Additional Information: | Funding Information: The work of Yi Ren was supported in part by the Engineering and Physical Sciences Research Council (EPSRC) under Grant EP/T022566/1 and Grant EP/T024593/1 and in part by the Royal Society IEC\R3\213100. The work of Jyh-Cheng Chen was supported in part by the National Science and Technology Council of Taiwan under Grant 111-2221-E-A49-093-MY3, Grant 111-2218-E-A49-023, and Grant 111-3114-E-A49-001. |
| Uncontrolled Keywords: | 3gpp standards,5g,multi-access edge computing,performance analysis,qos,multi-access edge computing,3gpp standards,performance analysis,applied mathematics,electrical and electronic engineering,computer science applications ,/dk/atira/pure/subjectarea/asjc/2600/2604 |
| Faculty \ School: | Faculty of Science > School of Computing Sciences |
| UEA Research Groups: | Faculty of Science > Research Groups > Smart Emerging Technologies Faculty of Science > Research Groups > Cyber Security Privacy and Trust Laboratory Faculty of Science > Research Groups > Data Science and AI |
| Related URLs: | |
| Depositing User: | LivePure Connector |
| Date Deposited: | 07 Mar 2023 17:30 |
| Last Modified: | 21 Dec 2024 01:06 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/91427 |
| DOI: | 10.1109/TWC.2023.3248270 |
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