EconPapers    
Economics at your fingertips  
 

Resource- and Time-Efficient Computation Offloading in Vehicular Edge Computing: A Max-Min Fairness Oriented Approach

Shujuan Wang, Hao Peng and Dongchao Guo ()
Additional contact information
Shujuan Wang: School of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China
Hao Peng: School of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China
Dongchao Guo: School of Computer Science, Beijing Information Science and Technology University, Beijing 100192, China

Mathematics, 2022, vol. 10, issue 20, 1-17

Abstract: Nowadays, computation offloading has become a research focus since it has the potential to solve the challenges faced when dealing with computation-intensive applications in the Internet of Vehicles (IoVs), especially in the 5G or future network environment. However, major issues still exist and the performance of main metrics can be improved to better adapt to the practical scenarios. This paper focuses on achieving resource- and time-efficient computation offloading in IoVs by boosting the cooperation efficiency of vehicles. Firstly, a fuzzy logic-based pricing strategy is designed to evaluate the cooperation tendency and capability of each vehicle from multiple aspects. Vehicles are encouraged to participate in the offloading process even if they are in a disadvantageous position compared to other vehicles. Secondly, a Max-Min fairness-oriented approach is proposed to find the most suitable offloading decision, and vehicles with poor cooperation capabilities are guaranteed to be treated equally in the offloading. Finally, two heuristic algorithms are presented to solve the problem with applicable complexity and to suit the practical IoV environment. Extensive simulation results prove that the proposed approach achieves remarkable performance improvements in terms of delay, service cost and the resource utilization ratios of vehicles.

Keywords: Internet of Vehicles; Vehicular Edge Computing; computation offloading; fuzzy logic; Max-Min fairness (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-7390/10/20/3735/pdf (application/pdf)
https://www.mdpi.com/2227-7390/10/20/3735/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:10:y:2022:i:20:p:3735-:d:938981

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().

 
Page updated 2025-03-19
Handle: RePEc:gam:jmathe:v:10:y:2022:i:20:p:3735-:d:938981