Internet of vehicles empowered by edge intelligence

Yan ZHANG; Ke ZHANG; Jiayu CAO

doi:10.11959/j.issn.2096-3750.2018.00080

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Internet of vehicles empowered by edge intelligence

Theory and Technology | 更新时间：2024-06-05

- Internet of vehicles empowered by edge intelligence
- Chinese Journal on Internet of Things Vol. 2, Issue 4, Pages: 40-48(2018)
- 作者机构：
  
  1. 挪威奥斯陆大学，挪威奥斯陆 0316
  2. 电子科技大学信息与通信工程学院，四川成都 611731
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.2096-3750.2018.00080
  CLC： TP319
- Published：30 December 2018，
  
  Published Online：2018-12，
- 稿件说明：
移动端阅览
YAN ZHANG, KE ZHANG, JIAYU CAO. Internet of vehicles empowered by edge intelligence. [J]. Chinese journal on internet of things, 2018, 2(4): 40-48.
DOI：

YAN ZHANG, KE ZHANG, JIAYU CAO. Internet of vehicles empowered by edge intelligence. [J]. Chinese journal on internet of things, 2018, 2(4): 40-48. DOI： 10.11959/j.issn.2096-3750.2018.00080.

摘要

边缘智能技术通过将计算、存储等资源向用户端推进的方式，赋予了网络边缘实体更强大的信息处理与内容投递能力，也为移动业务的开发与实现提供了高效、低时延的服务支撑平台，深刻地改变着移动应用的功能与网络资源的利用模式。首先对网络边缘智能技术在车联网中的应用进行研究，提出了设计高效车联边缘系统所需要解决的核心科学问题。然后，深入分析了以上问题解决过程中所面临的技术挑战，并给出了应对策略。

Abstract

By pushing computing

storage and other resources to the proximity of end devices

edge intelligence empowers network edge entities powerful information processing and content delivery capabilities

while providing efficient and low-latency service support for the development and implementation of novel mobile services.Thus

edge intelligence is profoundly changing the functions of mobile applications and the utilization patterns of network resources.The application of edge intelligence technology in vehicular networks was studied firstly

and the core scientific problems that need to be solved in designing an efficient vehicular edge system was presented.Then

the technical challenges faced in solving these problems were analyzed and the corresponding solution strategies were given.

关键词

边缘智能车联网资源协同区块链

Keywords

edge intelligencevehicular networkresource synergyblock chain

references

HUANG C, CHANG M, DAO D ,et al. V2V data offloading for cellular network based on the software defined network (SDN) inside mobile edge computing (MEC) architecture[J]. IEEE Access, 2018(6): 17741-17755.

CHENG N, XU W, SHI W ,et al. Air-ground integrated mobile edge networks:architecture,challenges and opportunities[J]. IEEE Communications Magazine, 2018,56(8): 26-32.

ZHANG L, ZHAO Z, WU Q ,et al. Energy-aware dynamic resource allocation in UAV assisted mobile edge computing over social Internet of vehicles[J]. IEEE Access, 2018

QIAO G, LENG S, ZHANG K ,et al. Collaborative task offloading in vehicular edge multi-access networks[J]. IEEE Communications Magazine, 2018,56(8): 48-54.

KLAIMI J, SENOUCI S, MESSOUS M . Theoretical game approach for mobile users resource management in a vehicular fog computing environment[C]// 2018 14th International Wireless Communications ＆Mobile Computing Conference (IWCMC),June 25-29,2018,Limassol,Cyprus. Piscataway:IEEE Press, 2018: 452-457.

李佐昭, 刘金旭 . 移动边缘计算在车联网中的应用[J]. 现代电信科技, 2018,47(3): 37-41.

LI Z Z, LIU J X . Application of mobile edge computing in Internet of vehicles[J]. Modern Science ＆ Technology Telecommunications, 2018,47(3): 37-41.

王紫薇 . 车联网数据内容分发与缓存技术研究[D]. 成都:西南交通大学, 2018.

WANG Z W . Research on data content distribution and caching technology in vehicle networking[D]. Chengdu:Southwest Jiaotong University, 2018.

IRFANULLAH K . 内容中心车联网中基于优先级的内容分发和缓存策略研究[D]. 北京:北京邮电大学, 2018.

IRFANULLAH K . Research on priority-based content distribution and caching strategy in content-centered vehicle networking[D]. Beijing:Beijing University of Posts and Telecommunications, 2018.

YU S, LANGAR R, FU X ,et al. Computation offloading with data caching enhancement for mobile edge computing[J]. IEEE Transactions on Vehicular Technology, 2018(99):1.

GUO Y, YANG Q, YU F R ,et al. Cache-enabled adaptive video streaming over vehicular networks:a dynamic approach[J]. IEEE Transactions on Vehicular Technology, 2018,67(6): 5445-5459.

SU Z, HUI Y, XU Q ,et al. An edge caching scheme to distribute content in vehicular networks[J]. IEEE Transactions on Vehicular Technology, 2018,67(6): 5346-5356.

LUO G, YUAN Q, ZHOU H ,et al. Cooperative vehicular content distribution in edge computing assisted 5G-VANET[J]. China Communications, 2018,15(7): 1-17.

JIAO J, HONG X, SHI J . Proactive content delivery for vehicles over cellular networks:the fundamental benefits of computing and caching[J]. China Communications, 2018,15(7): 88-97.

ZHAO Z, GUARDALBEN L, KARIMZADEH M ,et al. Mobilityprediction-assisted over-the-top edge prefetching for hierarchical VANET[J]. IEEE Journal on Selected Areas in Communications, 2018

LI M, YU F R, SI P ,et al. Software-defined vehicular networks with caching and computing for delay-tolerant data traffic[C]// 2018 IEEE International Conference on Communications (ICC),May 20-24,2018,Kansas City,USA. Piscataway:IEEE Press, 2018: 1-6.

LI M, SI P, ZHANG Y . Delay-tolerant data traffic to software-defined vehicular networks with mobile edge computing in smart city[J]. IEEE Transactions on Vehicular Technology, 2018,67(10): 9073-9086.

SHAH S A A, AHMED E, IMRAN M ,et al. 5G for vehicular communications[J]. IEEE Communications Magazine, 2018,56(1): 111-117.

HE Y, ZHAO N, YIN H . Integrated networking,caching and computing for connected vehicles:a deep reinforcement learning approach[J]. IEEE Transactions on Vehicular Technology, 2018,67(1): 44-55.

ZHANG K, LENG S, HE Y ,et al. Cooperative content caching in 5G networks with mobile edge computing[J]. IEEE Wireless Communications, 2018,25(3): 80-87.

YANG Q， GÜNDÜZ D . Coded caching and content delivery with heterogeneous distortion requirements[J]. IEEE Transactions on Information Theory, 2018,64(6): 4347-4364.

TAN Z, YU F R, LI X ,et al. Virtual resource allocation for heterogeneous services in full duplex-enabled SCNs with mobile edge computing and caching[J]. IEEE Transactions on Vehicular Technology, 2018,67(2): 1794-1808.

LE T T, HU R Q . Mobility-aware edge caching and computing in vehicle networks:a deep reinforcement learning[J]. IEEE Transactions on Vehicular Technology, 2018: 10190-10203.

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