Task offloading in vehicular edge computing networks via deep reinforcement learning

Elham Karimi; Yuanzhu Chen; Behzad Akbari

doi:10.1016/j.comcom.2022.04.006

ScienceGate Book Chapters

JOURNAL ARTICLE

Task offloading in vehicular edge computing networks via deep reinforcement learning

Elham Karimi Yuanzhu Chen Behzad Akbari

Year: 2022 Journal: Computer Communications Vol: 189 Pages: 193-204 Publisher: Elsevier BV

DOI: 10.1016/j.comcom.2022.04.006

Get Full-Text PDF Get Analytical Report

Keywords:

Computer science Reinforcement learning Cloud computing Distributed computing Enhanced Data Rates for GSM Evolution Edge computing Quality of service Task (project management) Edge device Resource allocation Scheme (mathematics) Vehicular ad hoc network Mobile edge computing Response time Computer network Artificial intelligence Wireless ad hoc network Telecommunications

Metrics

Cited By

13.71

FWCI (Field Weighted Citation Impact)

Refs

0.98

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

IoT and Edge/Fog Computing

Physical Sciences → Computer Science → Computer Networks and Communications

Blockchain Technology Applications and Security

Physical Sciences → Computer Science → Information Systems

Mobile Crowdsensing and Crowdsourcing

Physical Sciences → Computer Science → Computer Science Applications

Task offloading in vehicular edge computing networks via deep reinforcement learning

Metrics

Citation History

Topics

Related Documents

Deep reinforcement learning for task offloading in vehicular edge computing

Adaptive Task Offloading in Vehicular Edge Computing Networks Based on Deep Reinforcement Learning

Deep Reinforcement Learning-Guided Task Reverse Offloading in Vehicular Edge Computing

Task Offloading in Vehicular Edge Computing Network Using Deep Reinforcement Learning

Prioritized Task Offloading in Vehicular Edge Computing Using Deep Reinforcement Learning