Joint optimization algorithm for task offloading and resource allocation in low earth orbit satellites edge computing scenario
Aiming at the offloading requirements of ground users’ computing tasks in edge computing scenario of low earth orbit (LEO) satellites, a joint offloading and resource allocation optimization (JORAO) algorithm was proposed. Considering the limited coverage time of LEO satellites, the offloading strat...
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| Format: | Article |
| Language: | zho |
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Editorial Department of Journal on Communications
2024-07-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2024135/ |
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| author | XIA Weiwei HU Jing SONG Tiecheng |
| author_facet | XIA Weiwei HU Jing SONG Tiecheng |
| author_sort | XIA Weiwei |
| collection | DOAJ |
| description | Aiming at the offloading requirements of ground users’ computing tasks in edge computing scenario of low earth orbit (LEO) satellites, a joint offloading and resource allocation optimization (JORAO) algorithm was proposed. Considering the limited coverage time of LEO satellites, the offloading strategy, the allocation of communication and computing resources of LEO satellites were jointly optimized to minimize the average service delay of all ground users. The joint optimization problem of task offloading and resource allocation was decomposed into offloading decision and resource allocation sub-problems, and an alternating optimization method was used to obtain the suboptimal solution of the original optimization problem. The task offloading decision sub-problem was modeled as a coalition game model, and when the game reached Nash equilibrium, the ground user offloading strategy that minimized the system delay was obtained. For the resource allocation sub-problem, the Lagrange multiplier method was used to obtain the optimal bandwidth and compute resource allocation results. Moreover, the convergence and stability of the proposed algorithm were also demonstrated. The simulation results show that the proposed algorithm has excellent convergence and can significantly reduce the average service delay of ground users, as well as improve the task offloading success rate. |
| format | Article |
| id | doaj-art-424e6ad524834201837c6505c16ca444 |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2024-07-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-424e6ad524834201837c6505c16ca4442025-01-14T07:24:47ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2024-07-0145486067385062Joint optimization algorithm for task offloading and resource allocation in low earth orbit satellites edge computing scenarioXIA WeiweiHU JingSONG TiechengAiming at the offloading requirements of ground users’ computing tasks in edge computing scenario of low earth orbit (LEO) satellites, a joint offloading and resource allocation optimization (JORAO) algorithm was proposed. Considering the limited coverage time of LEO satellites, the offloading strategy, the allocation of communication and computing resources of LEO satellites were jointly optimized to minimize the average service delay of all ground users. The joint optimization problem of task offloading and resource allocation was decomposed into offloading decision and resource allocation sub-problems, and an alternating optimization method was used to obtain the suboptimal solution of the original optimization problem. The task offloading decision sub-problem was modeled as a coalition game model, and when the game reached Nash equilibrium, the ground user offloading strategy that minimized the system delay was obtained. For the resource allocation sub-problem, the Lagrange multiplier method was used to obtain the optimal bandwidth and compute resource allocation results. Moreover, the convergence and stability of the proposed algorithm were also demonstrated. The simulation results show that the proposed algorithm has excellent convergence and can significantly reduce the average service delay of ground users, as well as improve the task offloading success rate.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2024135/low earth orbit satelliteedge computingoffloadingresource allocationcoalition game |
| spellingShingle | XIA Weiwei HU Jing SONG Tiecheng Joint optimization algorithm for task offloading and resource allocation in low earth orbit satellites edge computing scenario Tongxin xuebao low earth orbit satellite edge computing offloading resource allocation coalition game |
| title | Joint optimization algorithm for task offloading and resource allocation in low earth orbit satellites edge computing scenario |
| title_full | Joint optimization algorithm for task offloading and resource allocation in low earth orbit satellites edge computing scenario |
| title_fullStr | Joint optimization algorithm for task offloading and resource allocation in low earth orbit satellites edge computing scenario |
| title_full_unstemmed | Joint optimization algorithm for task offloading and resource allocation in low earth orbit satellites edge computing scenario |
| title_short | Joint optimization algorithm for task offloading and resource allocation in low earth orbit satellites edge computing scenario |
| title_sort | joint optimization algorithm for task offloading and resource allocation in low earth orbit satellites edge computing scenario |
| topic | low earth orbit satellite edge computing offloading resource allocation coalition game |
| url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2024135/ |
| work_keys_str_mv | AT xiaweiwei jointoptimizationalgorithmfortaskoffloadingandresourceallocationinlowearthorbitsatellitesedgecomputingscenario AT hujing jointoptimizationalgorithmfortaskoffloadingandresourceallocationinlowearthorbitsatellitesedgecomputingscenario AT songtiecheng jointoptimizationalgorithmfortaskoffloadingandresourceallocationinlowearthorbitsatellitesedgecomputingscenario |