TY - JOUR
T1 - Toward Offloading Internet of Vehicles Applications in 5G Networks
AU - Wan, Shaohua
AU - Gu, Renhao
AU - Umer, Tariq
AU - Salah, Khaled
AU - Xu, Xiaolong
N1 - Funding Information:
Manuscript received January 22, 2020; revised July 4, 2020; accepted August 13, 2020. Date of publication September 1, 2020; date of current version July 12, 2021. This work was supported in part by the National Science Foundation of China under Grant 61702277, Grant 61772283, and Grant 61672276; in part by the Fundamental Research Funds for the Central Universities of China under Grant 2722019PY052; and in part by the Open Project from the State Key Laboratory for Novel Software Technology, Nanjing University, under Grant KFKT2019B17. The Associate Editor for this article was S. Mumtaz. (Corresponding author: Xiaolong Xu.) Shaohua Wan is with the School of Information and Safety Engineering, Zhongnan University of Economics and Law, Wuhan 430073, China.
Publisher Copyright:
© 2000-2011 IEEE.
PY - 2021/7
Y1 - 2021/7
N2 - The demand for real-time communication and high performance of the Internet of Vehicles (IoV) system has caused researches to investigate new techniques in edge computing (EC). With the rapid development of the fifth-generation (5G) network, the features of low delay, high reliability and superior communication efficiency can bring historic opportunities for the development of the EC-IoV system. In the 5G-enabled EC-IoV system, extreme densification of 5G base stations (gNBs) provides rapid and reliable network access and information interaction. However, this densification also brings more complex connectivity to the network, which increases the difficulty of resource migration and scheduling for the edge devices. Thus, it is still a challenge to manage the resources of the edge devices under the premise of reducing the energy and time cost in the system while avoiding the situation of overload or underload to maintain the stability of the system. In this article, a 5G-enabled EC-IoV system framework is proposed to enhance the performance of ∗the existing EC-IoV system. Specific computation offloading in 5G-enabled EC-IoV system is presented under three different cases. Through the above cases, two communication modes are concluded and the corresponding resource allocation strategy is given in this article. The performance of the proposed system is evaluated and compared with the existing system. Finally, future research directions in this area are considered.
AB - The demand for real-time communication and high performance of the Internet of Vehicles (IoV) system has caused researches to investigate new techniques in edge computing (EC). With the rapid development of the fifth-generation (5G) network, the features of low delay, high reliability and superior communication efficiency can bring historic opportunities for the development of the EC-IoV system. In the 5G-enabled EC-IoV system, extreme densification of 5G base stations (gNBs) provides rapid and reliable network access and information interaction. However, this densification also brings more complex connectivity to the network, which increases the difficulty of resource migration and scheduling for the edge devices. Thus, it is still a challenge to manage the resources of the edge devices under the premise of reducing the energy and time cost in the system while avoiding the situation of overload or underload to maintain the stability of the system. In this article, a 5G-enabled EC-IoV system framework is proposed to enhance the performance of ∗the existing EC-IoV system. Specific computation offloading in 5G-enabled EC-IoV system is presented under three different cases. Through the above cases, two communication modes are concluded and the corresponding resource allocation strategy is given in this article. The performance of the proposed system is evaluated and compared with the existing system. Finally, future research directions in this area are considered.
KW - Computation offloading
KW - edge computing (EC)
KW - fifth-generation (5G) networks
KW - Internet of Vehicles (IoV)
UR - http://www.scopus.com/inward/record.url?scp=85110882690&partnerID=8YFLogxK
U2 - 10.1109/TITS.2020.3017596
DO - 10.1109/TITS.2020.3017596
M3 - Article
AN - SCOPUS:85110882690
SN - 1524-9050
VL - 22
SP - 4151
EP - 4159
JO - IEEE Transactions on Intelligent Transportation Systems
JF - IEEE Transactions on Intelligent Transportation Systems
IS - 7
M1 - 9184262
ER -