Joint Task Offloading and Resource Allocation Strategy for DiffServ in Vehicular Cloud System
Joint Authors
Liu, Zhanjun
Kang, Ya
Dai, Yingdi
Chen, Qianbin
Source
Wireless Communications and Mobile Computing
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-11-02
Country of Publication
Egypt
No. of Pages
15
Main Subjects
Information Technology and Computer Science
Abstract EN
A vehicular cloud (VC) can reduce latency and improve resource utilization of the Internet of vehicles by effectively using the underutilized computing resources of nearby vehicles.
Although the task offloading of the VC enhances road safety and traffic management on the Internet of vehicles and meets the low-latency requirements for driving safety services on the Internet of vehicles business, there are still some key challenges such as the resource allocation mechanism of differentiated services (DiffServ) and task offloading mechanism of improving user experience.
To address these issues, we study the task offloading and resource allocation strategy of the VC system where tasks generated by vehicles can be offloaded and executed cooperatively by vehicles in VC.
Specifically, the computing task is further divided into independent subtasks and executed in different vehicles in VC to maximize the offloading utility.
Considering the mobility of vehicles, the deadline of tasks, and the limited computing resources, we propose the optimization problem of task offloading in the VC system in the cause of improved user experience.
To characterize the difference in service requirements resulting from the diversity of tasks, a DiffServ model focusing on the pricing of a task is utilized.
The initial pricing of a task is tailored by the characteristics of the task and the uniqueness of the network status.
In this model, tasks are sorted and processed in order according to task pricing, so as to optimize resource allocation.
Numerical results show that the proposed scheme can effectively increase the resource utilization and task completion ratio.
American Psychological Association (APA)
Kang, Ya& Liu, Zhanjun& Chen, Qianbin& Dai, Yingdi. 2020. Joint Task Offloading and Resource Allocation Strategy for DiffServ in Vehicular Cloud System. Wireless Communications and Mobile Computing،Vol. 2020, no. 2020, pp.1-15.
https://search.emarefa.net/detail/BIM-1214613
Modern Language Association (MLA)
Kang, Ya…[et al.]. Joint Task Offloading and Resource Allocation Strategy for DiffServ in Vehicular Cloud System. Wireless Communications and Mobile Computing No. 2020 (2020), pp.1-15.
https://search.emarefa.net/detail/BIM-1214613
American Medical Association (AMA)
Kang, Ya& Liu, Zhanjun& Chen, Qianbin& Dai, Yingdi. Joint Task Offloading and Resource Allocation Strategy for DiffServ in Vehicular Cloud System. Wireless Communications and Mobile Computing. 2020. Vol. 2020, no. 2020, pp.1-15.
https://search.emarefa.net/detail/BIM-1214613
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1214613