Efficient Mobility-Aware Task Offloading for Vehicular Edge Computing Networks
Vehicular networks are facing the challenges to support ubiquitous connections and high quality of service for numerous vehicles. To address these issues, mobile edge computing (MEC) is explored as a promising technology in vehicular networks by employing computing resources at the edge of vehicular...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2019-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8648330/ |
| _version_ | 1818854630177636352 |
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| author | Chao Yang Yi Liu Xin Chen Weifeng Zhong Shengli Xie |
| author_facet | Chao Yang Yi Liu Xin Chen Weifeng Zhong Shengli Xie |
| author_sort | Chao Yang |
| collection | DOAJ |
| description | Vehicular networks are facing the challenges to support ubiquitous connections and high quality of service for numerous vehicles. To address these issues, mobile edge computing (MEC) is explored as a promising technology in vehicular networks by employing computing resources at the edge of vehicular wireless access networks. In this paper, we study the efficient task offloading schemes in vehicular edge computing networks. The vehicles perform the offloading time selection, communication, and computing resource allocations optimally, the mobility of vehicles and the maximum latency of tasks are considered. To minimize the system costs, including the costs of the required communication and computing resources, we first analyze the offloading schemes in the independent MEC servers scenario. The offloading tasks are processed by the MEC servers deployed at the access point (AP) independently. A mobility-aware task offloading scheme is proposed. Then, in the cooperative MEC servers scenario, the MEC servers can further offload the collected overloading tasks to the adjacent servers at the next AP on the vehicles' moving direction. A location-based offloading scheme is proposed. In both scenarios, the tradeoffs between the task completed latency and the required communication and computation resources are mainly considered. Numerical results show that our proposed schemes can reduce the system costs efficiently, while the latency constraints are satisfied. |
| first_indexed | 2024-12-19T07:55:46Z |
| format | Article |
| id | doaj.art-23d38185e0d8476998c3bc75f401318a |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-19T07:55:46Z |
| publishDate | 2019-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-23d38185e0d8476998c3bc75f401318a2022-12-21T20:30:00ZengIEEEIEEE Access2169-35362019-01-017266522666410.1109/ACCESS.2019.29005308648330Efficient Mobility-Aware Task Offloading for Vehicular Edge Computing NetworksChao Yang0https://orcid.org/0000-0002-0335-2517Yi Liu1Xin Chen2https://orcid.org/0000-0001-7234-8135Weifeng Zhong3https://orcid.org/0000-0003-3588-2018Shengli Xie4https://orcid.org/0000-0003-2041-5214Guangdong Key Laboratory of IoT Information Technology, School of Automation, Guangdong University of Technology, Guangzhou, ChinaGuangdong Key Laboratory of IoT Information Technology, School of Automation, Guangdong University of Technology, Guangzhou, ChinaGuangdong Key Laboratory of IoT Information Technology, School of Automation, Guangdong University of Technology, Guangzhou, ChinaGuangdong Key Laboratory of IoT Information Technology, School of Automation, Guangdong University of Technology, Guangzhou, ChinaGuangdong Key Laboratory of IoT Information Technology, School of Automation, Guangdong University of Technology, Guangzhou, ChinaVehicular networks are facing the challenges to support ubiquitous connections and high quality of service for numerous vehicles. To address these issues, mobile edge computing (MEC) is explored as a promising technology in vehicular networks by employing computing resources at the edge of vehicular wireless access networks. In this paper, we study the efficient task offloading schemes in vehicular edge computing networks. The vehicles perform the offloading time selection, communication, and computing resource allocations optimally, the mobility of vehicles and the maximum latency of tasks are considered. To minimize the system costs, including the costs of the required communication and computing resources, we first analyze the offloading schemes in the independent MEC servers scenario. The offloading tasks are processed by the MEC servers deployed at the access point (AP) independently. A mobility-aware task offloading scheme is proposed. Then, in the cooperative MEC servers scenario, the MEC servers can further offload the collected overloading tasks to the adjacent servers at the next AP on the vehicles' moving direction. A location-based offloading scheme is proposed. In both scenarios, the tradeoffs between the task completed latency and the required communication and computation resources are mainly considered. Numerical results show that our proposed schemes can reduce the system costs efficiently, while the latency constraints are satisfied.https://ieeexplore.ieee.org/document/8648330/Vehicular networkedge computingresource allocationoffloadingmobility |
| spellingShingle | Chao Yang Yi Liu Xin Chen Weifeng Zhong Shengli Xie Efficient Mobility-Aware Task Offloading for Vehicular Edge Computing Networks IEEE Access Vehicular network edge computing resource allocation offloading mobility |
| title | Efficient Mobility-Aware Task Offloading for Vehicular Edge Computing Networks |
| title_full | Efficient Mobility-Aware Task Offloading for Vehicular Edge Computing Networks |
| title_fullStr | Efficient Mobility-Aware Task Offloading for Vehicular Edge Computing Networks |
| title_full_unstemmed | Efficient Mobility-Aware Task Offloading for Vehicular Edge Computing Networks |
| title_short | Efficient Mobility-Aware Task Offloading for Vehicular Edge Computing Networks |
| title_sort | efficient mobility aware task offloading for vehicular edge computing networks |
| topic | Vehicular network edge computing resource allocation offloading mobility |
| url | https://ieeexplore.ieee.org/document/8648330/ |
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