Asynchronous Deep Reinforcement Learning for Collaborative Task Computing and On-Demand Resource Allocation in Vehicular Edge Computing-Reference-Cited by-同舟云学术

Asynchronous Deep Reinforcement Learning for Collaborative Task Computing and On-Demand Resource Allocation in Vehicular Edge Computing

Author:

Liu Lei¹^ORCID,Feng Jie²^ORCID,Mu Xuanyu³,Pei Qingqi³^ORCID,Lan Dapeng⁴^ORCID,Xiao Ming⁵^ORCID

Affiliation:

1. Guangzhou Institute of Technology, Xidian University, Guangzhou, China

2. State Key Laboratory of Integrated Services Networks, School of Telecommunication Engineering, Xidian University, Xi’an, Shaanxi, China

3. State Key Laboratory of Integrated Services Networks, Xidian University, Xi’an, China

4. Department of Informatics, University of Oslo, Oslo, Norway

5. School of Electrical Engineering and Computer Science, Royal Institute of Technology, Stockholm, Sweden

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Key Research and Development Program of Shaanxi Province

Basic and Applied Basic Research Foundation of Guangdong Province

Guangdong High Level Innovation Reaearch Institution Project

China Postdoctoral Science Foundation

Key Laboratory of Embedded System and Service Computing (Tongji University);

Swedish Research Council Project

EU “Autonomous Vehicular Edge Computing and Networking for Intelligent Transportation (ASCENT)” Project

EU “Cooperative and Intelligent Unmanned Aerial Vehicles for Emergency Response Applications (COVER)” Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Science Applications,Mechanical Engineering,Automotive Engineering

Link

Reference46 articles.

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