Results 21 to 30 of about 2,179 (155)

Energy-Efficient Computation Offloading in Vehicular Edge Cloud Computing [PDF]

IEEE Access, 2020
With the development of electrification, automation, and interconnection of the automobile industry, the demand for vehicular computing has entered an explosive growth era. Massive low time-constrained and computation-intensive vehicular computing operations bring new challenges to vehicles, such as excessive computing power and energy consumption ...
Xin Li, Yifan Dang, Mohammad Aazam, Xia Peng, Tefang Chen, Chunyang Chen   +5 more
openaire   +2 more sources

A Survey on Vehicular Cloud Network Security

IEEE Access, 2023
The novel Vehicular Cloud Network (VCN) is a close combination of Vehicular Ad hoc Network, Cloud Computing, and Edge Computing. However, VCN is facing the enormous challenge of security and privacy before it is generalized.
Junyi Deng, Jikai Deng, Peihao Liu, Huan Wang, Junjie Yan, Deru Pan, Jiahua Liu   +6 more
doaj   +1 more source

Efficient Mobility-Aware Task Offloading for Vehicular Edge Computing Networks

IEEE Access, 2019
Vehicular networks are facing the challenges to support ubiquitous connections and high quality of service for numerous vehicles. To address these issues, mobile edge computing (MEC) is explored as a promising technology in vehicular networks by ...
Chao Yang, Yi Liu, Xin Chen, Weifeng Zhong, Shengli Xie   +4 more
doaj   +1 more source

Parked Vehicle Edge Computing: Exploiting Opportunistic Resources for Distributed Mobile Applications

IEEE Access, 2018
Vehicular Edge Computing (VEC) has been studied as an important application of mobile edge computing in vehicular networks. Usually, the generalization of VEC involves large-scale deployment of dedicated servers, which will cause tremendous economic ...
Xumin Huang, Rong Yu, Jianqi Liu, Lei Shu   +3 more
doaj   +1 more source

Software Defined Network-Based Multi-Access Edge Framework for Vehicular Networks

IEEE Access, 2020
Vehicular networks aim to support cooperative warning applications that involve the dissemination of warning messages to reach vehicles in a target area. Due to the high mobility of vehicles, imperative technologies such as software-defined network (SDN)
Lionel Nkenyereye, Lewis Nkenyereye, S. M. Riazul Islam, Chaker Abdelaziz Kerrache, M. Abdullah-Al-Wadud, Atif Alamri   +5 more
doaj   +1 more source

Computation Offloading for Vehicular Environments: A Survey

IEEE Access, 2020
With significant advances in communication and computing, modern day vehicles are becoming increasingly intelligent. This gives them the ability to contribute to safer roads and passenger comfort through network devices, cameras, sensors, and ...
Alisson Barbosa De Souza, Paulo A. L. Rego, Tiago Carneiro, Jardel Das C. Rodrigues, Pedro Pedrosa Reboucas Filho, Jose Neuman De Souza, Vinay Chamola, Victor Hugo C. De Albuquerque, Biplab Sikdar   +8 more
doaj   +1 more source

An anonymous access authentication scheme for vehicular ad hoc networks under edge computing

International Journal of Distributed Sensor Networks, 2018
With the rapid booming of intelligent traffic system, vehicular ad hoc networks have attracted wide attention from both academic and industry. However, security is the main obstacle for the wide deployment of vehicular ad hoc networks.
Tianhan Gao, Yanqiang Li, Nan Guo, Ilsun You   +3 more
doaj   +1 more source

Multipath Transmission Workload Balancing Optimization Scheme Based on Mobile Edge Computing in Vehicular Heterogeneous Network

IEEE Access, 2019
With the rapid development of intelligent transportation, various applications which have millisecond delay requirements appear in the vehicular heterogeneous network. Offloading these delay-sensitive applications into edge nodes is a trend and direction
Zhao Haitao, Ding Yi, Zhang Mengkang, Wang Qin, Shi Xinyue, Zhu Hongbo   +5 more
doaj   +1 more source

Computation Offloading for Mobile Edge Computing Enabled Vehicular Networks [PDF]

IEEE Access, 2019
The emergence of computation-intensive and delay-sensitive vehicular applications poses a great challenge for individual vehicles with limited computation resources. Mobile edge computing (MEC) is a new paradigm shift that can enhance vehicular services through computation offloading.
Jun Wang 0043, Daquan Feng, Shengli Zhang 0001, Jianhua Tang, Tony Q. S. Quek   +4 more
openaire   +2 more sources

An optimization scheme for vehicular edge computing based on Lyapunov function and deep reinforcement learning

IET Communications
Traditional vehicular edge computing research usually ignores the mobility of vehicles, the dynamic variability of the vehicular edge environment, the large amount of real‐time data required for vehicular edge computing, the limited resources of edge ...
Lin Zhu, Long Tan, Bingxian Li, Huizi Tian   +3 more
doaj   +1 more source