Cooperative optimisation strategy of computation offloading in multi‐UAVs‐assisted edge computing networks
Abstract Mobile edge computing has been developed as a promising technology to extend diverse services to the edge of the Internet of Things system. Motivated by the high flexibility and controllability of unmanned aerial vehicles (UAVs), a multi‐UAVs‐assisted mobile edge computing system is studied...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Wiley
2022-12-01
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| Series: | IET Communications |
| Online Access: | https://doi.org/10.1049/cmu2.12480 |
| _version_ | 1828335909079089152 |
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| author | Shanxin Zhang Runyu Cao Zefeng Jiang |
| author_facet | Shanxin Zhang Runyu Cao Zefeng Jiang |
| author_sort | Shanxin Zhang |
| collection | DOAJ |
| description | Abstract Mobile edge computing has been developed as a promising technology to extend diverse services to the edge of the Internet of Things system. Motivated by the high flexibility and controllability of unmanned aerial vehicles (UAVs), a multi‐UAVs‐assisted mobile edge computing system is studied to reduce the total consumption of time and energy of terminal equipments. In this system, UAVs act as the computing nodes or relay nodes for process terminal equipment's task. Accordingly, an optimisation problem is formulated to minimise the weighted sum of energy and delay consumption in the edge computing network. To solve the problem, an asynchronous advantage actor–critic (A3C) based deep reinforcement learning algorithm is proposed to obtain the optimal strategy for computation offloading and resource allocation. Experimental results demonstrate that the proposed A3C based algorithm converges fast and outperforms the baseline algorithms in terms of the energy and time consumption of system. |
| first_indexed | 2024-04-13T21:53:07Z |
| format | Article |
| id | doaj.art-dbbae6059367474a889ce766647689b0 |
| institution | Directory Open Access Journal |
| issn | 1751-8628 1751-8636 |
| language | English |
| last_indexed | 2024-04-13T21:53:07Z |
| publishDate | 2022-12-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Communications |
| spelling | doaj.art-dbbae6059367474a889ce766647689b02022-12-22T02:28:21ZengWileyIET Communications1751-86281751-86362022-12-0116192265227710.1049/cmu2.12480Cooperative optimisation strategy of computation offloading in multi‐UAVs‐assisted edge computing networksShanxin Zhang0Runyu Cao1Zefeng Jiang2Engineering Research Center of Internet of Things Technology Applications of the Ministry of Education School of Internet of Things Engineering Jiangnan University Wuxi People's Republic of ChinaEngineering Research Center of Internet of Things Technology Applications of the Ministry of Education School of Internet of Things Engineering Jiangnan University Wuxi People's Republic of ChinaEngineering Research Center of Internet of Things Technology Applications of the Ministry of Education School of Internet of Things Engineering Jiangnan University Wuxi People's Republic of ChinaAbstract Mobile edge computing has been developed as a promising technology to extend diverse services to the edge of the Internet of Things system. Motivated by the high flexibility and controllability of unmanned aerial vehicles (UAVs), a multi‐UAVs‐assisted mobile edge computing system is studied to reduce the total consumption of time and energy of terminal equipments. In this system, UAVs act as the computing nodes or relay nodes for process terminal equipment's task. Accordingly, an optimisation problem is formulated to minimise the weighted sum of energy and delay consumption in the edge computing network. To solve the problem, an asynchronous advantage actor–critic (A3C) based deep reinforcement learning algorithm is proposed to obtain the optimal strategy for computation offloading and resource allocation. Experimental results demonstrate that the proposed A3C based algorithm converges fast and outperforms the baseline algorithms in terms of the energy and time consumption of system.https://doi.org/10.1049/cmu2.12480 |
| spellingShingle | Shanxin Zhang Runyu Cao Zefeng Jiang Cooperative optimisation strategy of computation offloading in multi‐UAVs‐assisted edge computing networks IET Communications |
| title | Cooperative optimisation strategy of computation offloading in multi‐UAVs‐assisted edge computing networks |
| title_full | Cooperative optimisation strategy of computation offloading in multi‐UAVs‐assisted edge computing networks |
| title_fullStr | Cooperative optimisation strategy of computation offloading in multi‐UAVs‐assisted edge computing networks |
| title_full_unstemmed | Cooperative optimisation strategy of computation offloading in multi‐UAVs‐assisted edge computing networks |
| title_short | Cooperative optimisation strategy of computation offloading in multi‐UAVs‐assisted edge computing networks |
| title_sort | cooperative optimisation strategy of computation offloading in multi uavs assisted edge computing networks |
| url | https://doi.org/10.1049/cmu2.12480 |
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