A Deep Reinforcement Learning Approach For Data Migration in Multi-Access Edge Computing
- 1 November 2018
- conference paper
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
Abstract
No abstract availableThis publication has 8 references indexed in Scilit:
- A 5G-Enabling Technology: Benefits, Feasibility, and Limitations of In-Band Full-Duplex mMIMOIEEE Vehicular Technology Magazine, 2018
- Data Processing in Cyber-Physical-Social Systems Through Edge ComputingIEEE Access, 2018
- Machine learning‐based IDS for software‐defined 5G networkIET Networks, 2018
- I/Ocloud: Adding an IoT Dimension to Cloud InfrastructuresComputer, 2018
- A migration-enhanced edge computing support for mobile devices in hostile environmentsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2017
- Multi-agent and reinforcement learning based code offloading in mobile fogPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2016
- Human-level control through deep reinforcement learningNature, 2015
- AN OVERVIEW OF THE OMNeT++ SIMULATION ENVIRONMENTPublished by European Alliance for Innovation n.o. ,2008