Task Offloading Based on Lyapunov Optimization for MEC-Assisted Vehicular Platooning Networks
Due to limited computation resources of a vehicle terminal, it is impossible to meet the demands of some applications and services, especially for computation-intensive types, which not only results in computation burden and delay, but also consumes more energy. Mobile edge computing (MEC) is an eme...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-11-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/19/22/4974 |
| _version_ | 1798003767245799424 |
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| author | Taiping Cui Yuyu Hu Bin Shen Qianbin Chen |
| author_facet | Taiping Cui Yuyu Hu Bin Shen Qianbin Chen |
| author_sort | Taiping Cui |
| collection | DOAJ |
| description | Due to limited computation resources of a vehicle terminal, it is impossible to meet the demands of some applications and services, especially for computation-intensive types, which not only results in computation burden and delay, but also consumes more energy. Mobile edge computing (MEC) is an emerging architecture in which computation and storage services are extended to the edge of a network, which is an advanced technology to support multiple applications and services that requires ultra-low latency. In this paper, a task offloading approach for an MEC-assisted vehicle platooning is proposed, where the Lyapunov optimization algorithm is employed to solve the optimization problem under the condition of stability of task queues. The proposed approach dynamically adjusts the offloading decisions for all tasks according to data parameters of current task, and judge whether it is executed locally, in other platooning member or at an MEC server. The simulation results show that the proposed algorithm can effectively reduce energy consumption of task execution and greatly improve the offloading efficiency compared with the shortest queue waiting time algorithm and the full offloading to an MEC algorithm. |
| first_indexed | 2024-04-11T12:14:05Z |
| format | Article |
| id | doaj.art-9cf46430557f423293054077a8d2098e |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T12:14:05Z |
| publishDate | 2019-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-9cf46430557f423293054077a8d2098e2022-12-22T04:24:28ZengMDPI AGSensors1424-82202019-11-011922497410.3390/s19224974s19224974Task Offloading Based on Lyapunov Optimization for MEC-Assisted Vehicular Platooning NetworksTaiping Cui0Yuyu Hu1Bin Shen2Qianbin Chen3School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Nan-An District, Chongqing 400065, ChinaSchool of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Nan-An District, Chongqing 400065, ChinaSchool of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Nan-An District, Chongqing 400065, ChinaChongqing Key Labs of Mobile Communications, Chongqing 400065, ChinaDue to limited computation resources of a vehicle terminal, it is impossible to meet the demands of some applications and services, especially for computation-intensive types, which not only results in computation burden and delay, but also consumes more energy. Mobile edge computing (MEC) is an emerging architecture in which computation and storage services are extended to the edge of a network, which is an advanced technology to support multiple applications and services that requires ultra-low latency. In this paper, a task offloading approach for an MEC-assisted vehicle platooning is proposed, where the Lyapunov optimization algorithm is employed to solve the optimization problem under the condition of stability of task queues. The proposed approach dynamically adjusts the offloading decisions for all tasks according to data parameters of current task, and judge whether it is executed locally, in other platooning member or at an MEC server. The simulation results show that the proposed algorithm can effectively reduce energy consumption of task execution and greatly improve the offloading efficiency compared with the shortest queue waiting time algorithm and the full offloading to an MEC algorithm.https://www.mdpi.com/1424-8220/19/22/4974mobile edge computingvehicular platooningtask offloadinglyapunov optimization |
| spellingShingle | Taiping Cui Yuyu Hu Bin Shen Qianbin Chen Task Offloading Based on Lyapunov Optimization for MEC-Assisted Vehicular Platooning Networks Sensors mobile edge computing vehicular platooning task offloading lyapunov optimization |
| title | Task Offloading Based on Lyapunov Optimization for MEC-Assisted Vehicular Platooning Networks |
| title_full | Task Offloading Based on Lyapunov Optimization for MEC-Assisted Vehicular Platooning Networks |
| title_fullStr | Task Offloading Based on Lyapunov Optimization for MEC-Assisted Vehicular Platooning Networks |
| title_full_unstemmed | Task Offloading Based on Lyapunov Optimization for MEC-Assisted Vehicular Platooning Networks |
| title_short | Task Offloading Based on Lyapunov Optimization for MEC-Assisted Vehicular Platooning Networks |
| title_sort | task offloading based on lyapunov optimization for mec assisted vehicular platooning networks |
| topic | mobile edge computing vehicular platooning task offloading lyapunov optimization |
| url | https://www.mdpi.com/1424-8220/19/22/4974 |
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