Edge Intelligence for Multi-Dimensional Resource Management in Aerial-Assisted Vehicular Networks

被引：18

作者：

Peng, Haixia ^{[1
]}

Wu, Huaqing ^{[2
]}

Shen, Xuemin Sherman ^{[3
]}

机构：

[1] Calif State Univ Long Beach, Dept Comp Engn & Comp Sci, Long Beach, CA 90840 USA

[2] Univ Waterloo, Waterloo, ON, Canada

[3] Univ Waterloo, Dept Elect & Comp Engn, Waterloo, ON, Canada

来源：

IEEE WIRELESS COMMUNICATIONS | 2021年 / 28卷 / 05期

关键词：

Adaptive systems; Quality of service; Computer architecture; Dynamic scheduling; Resource management; Vehicle dynamics; Artificial intelligence; CHALLENGES;

D O I：

10.1109/MWC.101.2100056

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

A new architecture with drone-assisted multi-access edge computing (MEC) is proposed for vehicular networks to support computation-intensive and delay-sensitive applications and services. Artificial intelligence (AI)-based resource management schemes are developed such that terrestrial and aerial spectrum, computing, and storage resources can be cooperatively allocated for guaranteeing the quality of service requirements from different applications. A case study on the joint management of the spectrum and computing resources is presented to demonstrate the effectiveness of AI-based resource management schemes.

引用

页码：59 / 65

页数：7

共 11 条

[1]

Chen Xinlei, 2020, AUTOPHAGY, DOI DOI 10.1080/15548627.2020.1810918

[2] Multi-Armed Bandit Learning for Computation-Intensive Services in MEC-Empowered Vehicular Networks [J].

Dai, Penglin ;

Hang, Zihua ;

Liu, Kai ;

Wu, Xiao ;

Xing, Huanlai ;

Yu, Zhaofei ;

Lee, Victor Chung Sing .

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2020, 69 (07) :7821-7834

[3] Joint Resources and Workflow Scheduling in UAV-Enabled Wirelessly-Powered MEC for IoT Systems [J].

Du, Yao ;

Yang, Kun ;

Wang, Kezhi ;

Zhang, Guopeng ;

Zhao, Yizhe ;

Chen, Dongwei .

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2019, 68 (10) :10187-10200

[4] Ultra-Reliable Low-Latency Communications in Autonomous Vehicular Networks [J].

Ge, Xiaohu .

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2019, 68 (05) :5005-5016

[5] Multi-access edge computing: The driver behind the wheel of 5g-connected cars [J].

Giust F. ;

Sciancalepore V. ;

Sabella D. ;

Filippou M.C. ;

Mangiante S. ;

Featherstone W. ;

Munaretto D. .

IEEE Communications Standards Magazine, 2018, 2 (03) :66-73

[6]

Haarnoja T., 2019, SOFT ACTOR CRITIC AL

[7]

Kulkarni TD, 2016, ADV NEUR IN, V29

[8] Multi-Agent Reinforcement Learning Based Resource Management in MEC- and UAV-Assisted Vehicular Networks [J].

Peng, Haixia ;

Shen, Xuemin .

IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, 2021, 39 (01) :131-141

[9] Drone Assisted Vehicular Networks: Architecture, Challenges and Opportunities [J].

Shi, Weisen ;

Zhou, Haibo ;

Li, Junling ;

Xu, Wenchao ;

Zhang, Ning ;

Shen, Xuemin .

IEEE NETWORK, 2018, 32 (03) :130-137

[10] Software Defined Space-Air-Ground Integrated Vehicular Networks: Challenges and Solutions [J].

Zhang, Ning ;

Zhang, Shan ;

Yang, Peng ;

Alhussein, Omar ;

Zhuang, Weihua ;

Shen, Xuemin .

IEEE COMMUNICATIONS MAGAZINE, 2017, 55 (07) :101-109

← 1 2 →