Virtual edge: Exploring computation offloading in collaborative vehicular edge computing

41Citations
Citations of this article
30Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Vehicular edge computing (VEC) has been a new paradigm to support computation-intensive and latency-sensitive services. However, the scarcity of computational resources is still a challenge. Making efficient use of sporadic idle computational resources on smart vehicles in the vicinity to extend the resource capability of each vehicle is an important research issue. In this paper, we propose Virtual Edge, which is an efficient scheme to utilize free computational resources of multiple vehicles as a virtual server to facilitate collaborative vehicular edge computing. We design a virtual edge formation algorithm that considers both the stability of virtual edge and the computational resources available at the vehicles constituting the virtual edge. The prediction of the link duration between vehicles reduces the number of computation offloading failures caused by unexpected link disconnections. Extensive simulations with realistic vehicle movements are conducted to show the advantage of the proposed scheme over existing baselines in terms of the completion ratio of computation offloading tasks and average task execution time.

References Powered by Scopus

A Survey on Mobile Edge Computing: The Communication Perspective

4307Citations
N/AReaders
Get full text

Mobile Edge Computing: A Survey on Architecture and Computation Offloading

2658Citations
N/AReaders
Get full text

Energy-Efficient Resource Allocation for Mobile-Edge Computation Offloading

1378Citations
N/AReaders
Get full text

Cited by Powered by Scopus

Efficient task offloading using particle swarm optimization algorithm in edge computing for industrial internet of things

103Citations
N/AReaders
Get full text

Task offloading paradigm in mobile edge computing-current issues, adopted approaches, and future directions

84Citations
N/AReaders
Get full text

Learning Based Energy Efficient Task Offloading for Vehicular Collaborative Edge Computing

62Citations
N/AReaders
Get full text

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

Cha, N., Wu, C., Yoshinaga, T., Ji, Y., & Alvin Yau, K. L. (2021). Virtual edge: Exploring computation offloading in collaborative vehicular edge computing. IEEE Access, 9, 37739–37751. https://doi.org/10.1109/ACCESS.2021.3063246

Readers over time

‘21‘22‘23‘24‘2505101520

Readers' Seniority

Tooltip

PhD / Post grad / Masters / Doc 14

70%

Researcher 4

20%

Professor / Associate Prof. 1

5%

Lecturer / Post doc 1

5%

Readers' Discipline

Tooltip

Computer Science 18

86%

Engineering 3

14%

Save time finding and organizing research with Mendeley

Sign up for free
0