Real-Time and Low-Overhead Graph Task Scheduling over Vehicular Computing-Assisted Edge Networks-Reference-Cited by-同舟云学术

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Real-Time and Low-Overhead Graph Task Scheduling over Vehicular Computing-Assisted Edge Networks

Published:2024-06-09 Issue: Volume: Page:4930-4935
ISSN:
Container-title:ICC 2024 - IEEE International Conference on Communications
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Author:

Guo Bingshuo¹,Liwang Minghui¹,Yang Fan¹,Hosseinalipour Seyyedali²,Wang Xianbin³,Dai Huaiyu⁴

Affiliation:

1. Xiamen University,Dept. of Information and Communication Engineering,Xiamen,China

2. University at Buffalo-SUNY,Dept. of Electrical Engineering,NY,USA

3. Western University,Dept. of Electrical and Computer Engineering,Ontario,Canada

4. North Carolina State University,Dept. of Electrical and Computer Engineering,Raleigh,USA

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10622104/10622158/10622213.pdf?arnumber=10622213

Reference16 articles.

1. Multi-Task Offloading over Vehicular Clouds under Graph-based Representation

2. Energy-Efficient Computation Offloading in Vehicular Edge Cloud Computing

3. Dependency-Aware Task Scheduling in Vehicular Edge Computing

4. A Distributed Vehicle-assisted Computation Offloading Scheme based on DRL in Vehicular Networks

5. Low-latency Scheduling Approach for Dependent Tasks in MEC-enabled 5G Vehicular Networks

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