Joint Offloading Decision and Resource Allocation in Mobile Edge Computing-Enabled Satellite-Terrestrial Network
With the development of satellite-terrestrial network (STN), mobile edge computing (MEC) servers are deployed at low orbit earth (LEO) satellites to provide computing services for user devices (UEs) in areas without terrestrial network coverage. There is symmetry between satellite networks and terre...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-03-01
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| Series: | Symmetry |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2073-8994/14/3/564 |
| _version_ | 1797441569045872640 |
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| author | Minglei Tong Xiaoxiang Wang Song Li Liang Peng |
| author_facet | Minglei Tong Xiaoxiang Wang Song Li Liang Peng |
| author_sort | Minglei Tong |
| collection | DOAJ |
| description | With the development of satellite-terrestrial network (STN), mobile edge computing (MEC) servers are deployed at low orbit earth (LEO) satellites to provide computing services for user devices (UEs) in areas without terrestrial network coverage. There is symmetry between satellite networks and terrestrial networks, but there is asymmetry between their resources. Computing resources of satellites’ MEC servers may not be enough. The satellite-terrestrial cooperation is promising, where a satellite migrates tasks to a base station (BS) in an adjacent area, thus utilizing computing resources of the BS’s MEC server. Although there are some studies on computation offloading in STN, few studies consider a satellite as both a relay and a computing unit to assist UEs in computing tasks. This paper proposes a joint offloading decision and resource allocation scheme in MEC-enabled STN, which minimizes the completion delay of all UEs’ indivisible tasks. Firstly, the optimization problem is formulated and decomposed. Then, the proposed scheme based on potential game and the Lagrange multiplier method makes UEs’ task offloading decisions and allocates the satellite’s and the BS’s computing resources, thus obtaining the optimal solution through continuous iterations. Finally, the simulation results validate that the proposed scheme can obtain better gain than other baseline schemes. |
| first_indexed | 2024-03-09T12:25:02Z |
| format | Article |
| id | doaj.art-a3372db4d8914f51a0553ac06db24b66 |
| institution | Directory Open Access Journal |
| issn | 2073-8994 |
| language | English |
| last_indexed | 2024-03-09T12:25:02Z |
| publishDate | 2022-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Symmetry |
| spelling | doaj.art-a3372db4d8914f51a0553ac06db24b662023-11-30T22:36:23ZengMDPI AGSymmetry2073-89942022-03-0114356410.3390/sym14030564Joint Offloading Decision and Resource Allocation in Mobile Edge Computing-Enabled Satellite-Terrestrial NetworkMinglei Tong0Xiaoxiang Wang1Song Li2Liang Peng3School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaSchool of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaSchool of Information and Control Engineering, China University of Mining and Technology, Xuzhou 221116, ChinaSchool of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaWith the development of satellite-terrestrial network (STN), mobile edge computing (MEC) servers are deployed at low orbit earth (LEO) satellites to provide computing services for user devices (UEs) in areas without terrestrial network coverage. There is symmetry between satellite networks and terrestrial networks, but there is asymmetry between their resources. Computing resources of satellites’ MEC servers may not be enough. The satellite-terrestrial cooperation is promising, where a satellite migrates tasks to a base station (BS) in an adjacent area, thus utilizing computing resources of the BS’s MEC server. Although there are some studies on computation offloading in STN, few studies consider a satellite as both a relay and a computing unit to assist UEs in computing tasks. This paper proposes a joint offloading decision and resource allocation scheme in MEC-enabled STN, which minimizes the completion delay of all UEs’ indivisible tasks. Firstly, the optimization problem is formulated and decomposed. Then, the proposed scheme based on potential game and the Lagrange multiplier method makes UEs’ task offloading decisions and allocates the satellite’s and the BS’s computing resources, thus obtaining the optimal solution through continuous iterations. Finally, the simulation results validate that the proposed scheme can obtain better gain than other baseline schemes.https://www.mdpi.com/2073-8994/14/3/564satellite-terrestrial networkmobile edge computingsatellite-terrestrial cooperationoffloading decisionresource allocation |
| spellingShingle | Minglei Tong Xiaoxiang Wang Song Li Liang Peng Joint Offloading Decision and Resource Allocation in Mobile Edge Computing-Enabled Satellite-Terrestrial Network Symmetry satellite-terrestrial network mobile edge computing satellite-terrestrial cooperation offloading decision resource allocation |
| title | Joint Offloading Decision and Resource Allocation in Mobile Edge Computing-Enabled Satellite-Terrestrial Network |
| title_full | Joint Offloading Decision and Resource Allocation in Mobile Edge Computing-Enabled Satellite-Terrestrial Network |
| title_fullStr | Joint Offloading Decision and Resource Allocation in Mobile Edge Computing-Enabled Satellite-Terrestrial Network |
| title_full_unstemmed | Joint Offloading Decision and Resource Allocation in Mobile Edge Computing-Enabled Satellite-Terrestrial Network |
| title_short | Joint Offloading Decision and Resource Allocation in Mobile Edge Computing-Enabled Satellite-Terrestrial Network |
| title_sort | joint offloading decision and resource allocation in mobile edge computing enabled satellite terrestrial network |
| topic | satellite-terrestrial network mobile edge computing satellite-terrestrial cooperation offloading decision resource allocation |
| url | https://www.mdpi.com/2073-8994/14/3/564 |
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