Software-Defined Optimal Computation Task Scheduling in Vehicular Edge Networking
With the development of smart vehicles and various vehicular applications, Vehicular Edge Computing (VEC) paradigm has attracted from academic and industry. Compared with the cloud computing platform, VEC has several new features, such as the higher network bandwidth and the lower transmission delay...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-02-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/21/3/955 |
| _version_ | 1797417162933010432 |
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| author | Zhiyuan Li Ershuai Peng |
| author_facet | Zhiyuan Li Ershuai Peng |
| author_sort | Zhiyuan Li |
| collection | DOAJ |
| description | With the development of smart vehicles and various vehicular applications, Vehicular Edge Computing (VEC) paradigm has attracted from academic and industry. Compared with the cloud computing platform, VEC has several new features, such as the higher network bandwidth and the lower transmission delay. Recently, vehicular computation-intensive task offloading has become a new research field for the vehicular edge computing networks. However, dynamic network topology and the bursty computation tasks offloading, which causes to the computation load unbalancing for the VEC networking. To solve this issue, this paper proposed an optimal control-based computing task scheduling algorithm. Then, we introduce software defined networking/OpenFlow framework to build a software-defined vehicular edge networking structure. The proposed algorithm can obtain global optimum results and achieve the load-balancing by the virtue of the global load status information. Besides, the proposed algorithm has strong adaptiveness in dynamic network environments by automatic parameter tuning. Experimental results show that the proposed algorithm can effectively improve the utilization of computation resources and meet the requirements of computation and transmission delay for various vehicular tasks. |
| first_indexed | 2024-03-09T06:14:53Z |
| format | Article |
| id | doaj.art-947dad6bae2e4292b906c01f49ab8b5e |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T06:14:53Z |
| publishDate | 2021-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-947dad6bae2e4292b906c01f49ab8b5e2023-12-03T11:54:28ZengMDPI AGSensors1424-82202021-02-0121395510.3390/s21030955Software-Defined Optimal Computation Task Scheduling in Vehicular Edge NetworkingZhiyuan Li0Ershuai Peng1College of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang 212013, ChinaCollege of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang 212013, ChinaWith the development of smart vehicles and various vehicular applications, Vehicular Edge Computing (VEC) paradigm has attracted from academic and industry. Compared with the cloud computing platform, VEC has several new features, such as the higher network bandwidth and the lower transmission delay. Recently, vehicular computation-intensive task offloading has become a new research field for the vehicular edge computing networks. However, dynamic network topology and the bursty computation tasks offloading, which causes to the computation load unbalancing for the VEC networking. To solve this issue, this paper proposed an optimal control-based computing task scheduling algorithm. Then, we introduce software defined networking/OpenFlow framework to build a software-defined vehicular edge networking structure. The proposed algorithm can obtain global optimum results and achieve the load-balancing by the virtue of the global load status information. Besides, the proposed algorithm has strong adaptiveness in dynamic network environments by automatic parameter tuning. Experimental results show that the proposed algorithm can effectively improve the utilization of computation resources and meet the requirements of computation and transmission delay for various vehicular tasks.https://www.mdpi.com/1424-8220/21/3/955software-defined vehicular edge networkingresource allocationcomputation task schedulingoptimal control |
| spellingShingle | Zhiyuan Li Ershuai Peng Software-Defined Optimal Computation Task Scheduling in Vehicular Edge Networking Sensors software-defined vehicular edge networking resource allocation computation task scheduling optimal control |
| title | Software-Defined Optimal Computation Task Scheduling in Vehicular Edge Networking |
| title_full | Software-Defined Optimal Computation Task Scheduling in Vehicular Edge Networking |
| title_fullStr | Software-Defined Optimal Computation Task Scheduling in Vehicular Edge Networking |
| title_full_unstemmed | Software-Defined Optimal Computation Task Scheduling in Vehicular Edge Networking |
| title_short | Software-Defined Optimal Computation Task Scheduling in Vehicular Edge Networking |
| title_sort | software defined optimal computation task scheduling in vehicular edge networking |
| topic | software-defined vehicular edge networking resource allocation computation task scheduling optimal control |
| url | https://www.mdpi.com/1424-8220/21/3/955 |
| work_keys_str_mv | AT zhiyuanli softwaredefinedoptimalcomputationtaskschedulinginvehicularedgenetworking AT ershuaipeng softwaredefinedoptimalcomputationtaskschedulinginvehicularedgenetworking |