Open Access
ARTICLE
An Optimization Scheme for Task Offloading and Resource Allocation in Vehicle Edge Networks
Yuxin Xu1, Zilong Jin1,2,*, Xiaorui Zhang1, Lejun Zhang3
1 School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing, 210044, China
2Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science and Technology, Nanjing, 210044, China
3 College of Information Engineering, Yangzhou University, Yangzhou, 225127, China
* Corresponding Author: Zilong Jin. Email:
Journal on Internet of Things 2020, 2(4), 163-173. https://doi.org/10.32604/jiot.2020.011792
Received 20 May 2020; Accepted 15 August 2020; Issue published 22 September 2020
Abstract
The vehicle edge network (VEN) has become a new research hotspot
in the Internet of Things (IOT). However, many new delays are generated during
the vehicle offloading the task to the edge server, which will greatly reduce the
quality of service (QOS) provided by the vehicle edge network. To solve this
problem, this paper proposes an evolutionary algorithm-based (EA) task
offloading and resource allocation scheme. First, the delay of offloading task to
the edge server is generally defined, then the mathematical model of problem is
given. Finally, the objective function is optimized by evolutionary algorithm,
and the optimal solution is obtained by iteration and averaging. To verify the
performance of this method, contrast experiments are conducted. The
experimental results show that our purposed method reduces delay and improves
QOS, which is superior to other schemes.
Keywords
Cite This Article
Y. Xu, Z. Jin, X. Zhang and L. Zhang, "An optimization scheme for task offloading and resource allocation in vehicle edge networks,"
Journal on Internet of Things, vol. 2, no.4, pp. 163–173, 2020.