A Survey on Task Partitioning and Scheduling for Vehicular Edge Computing-Reference-Cited by-同舟云学术

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A Survey on Task Partitioning and Scheduling for Vehicular Edge Computing

Published:2023-07 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE 10th International Conference on Cyber Security and Cloud Computing (CSCloud)/2023 IEEE 9th International Conference on Edge Computing and Scalable Cloud (EdgeCom)
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Author:

Huang Jing¹,Wu Wenyu¹,Huang Weihong¹,Xiao Yufeng¹,Lisi Li²,Sun Jinxi¹

Affiliation:

1. Hunan University of Science and Technology Hunan Key Laboratory for Service Computing and Novel Software Technology,School of Computer Science and Engineering,Xiangtan,China,411201

2. The Bilingual Experimental School Attached to HNSDFZ,Changsha,China,410006

Funder

Hunan University of Science and Technology

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10195194/10195273/10195282.pdf?arnumber=10195282

Reference48 articles.

1. Deep Learning Empowered Task Offloading for Mobile Edge Computing in Urban Informatics

2. Vehicular and Edge Computing for Emerging Connected and Autonomous Vehicle Applications

3. Deep Reinforcement Learning for Collaborative Edge Computing in Vehicular Networks

4. Mobility-Aware Multi-Hop Task Offloading for Autonomous Driving in Vehicular Edge Computing and Networks

5. Joint Task Offloading and Resource Allocation in UAV-Enabled Mobile Edge Computing

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1. Edge Video Analytics: A Survey on Applications, Systems and Enabling Techniques;IEEE Communications Surveys & Tutorials;2023

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