Deep Reinforcement Learning Based Delay-Sensitive Task Scheduling and Resource Management Algorithm for Multi-User Mobile-Edge Computing Systems-Reference-Cited by-同舟云学术

Deep Reinforcement Learning Based Delay-Sensitive Task Scheduling and Resource Management Algorithm for Multi-User Mobile-Edge Computing Systems

Published:2019 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2019 4th International Conference on Mathematics and Artificial Intelligence - ICMAI 2019
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Author:

Meng Hao¹,Chao Daichong¹,Huo Ru¹,Guo Qianying¹,Li Xiaowei¹,Huang Tao²

Affiliation:

1. Beijing Advanced Innovation Center for Future Internet Technology, Beijing University of Technology, Beijing, China

2. State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China

Publisher

ACM Press

Reference16 articles.

1. Liu, J., Mao, Y., Zhang, J., and Letaief, K. B. 2016. Delay-optimal computation task scheduling for mobile-edge computing systems. DOI= http://dx.doi.org/10.1109/ISIT.2016.7541539

2. Kamoun, M., Labidi, W., and Sarkiss, M. 2018. Joint resource allocation and offloading strategies in cloud enabled cellular networks. IEEE International Conference on Communications. DOI= http://dx.doi.org/10.1109/ICC.2015.7249203

3. Labidi, W., Sarkiss, M., and Kamoun, M. 2015. Energy-optimal resource scheduling and computation offloading in small cell networks. International Conference on Telecommunications. IEEE. DOI= http://dx.doi.org/10.1109/ICT.2015.7124703

4. You, C., and Huang, K. 2017. Multiuser Resource Allocation for Mobile-Edge Computation Offloading. Global Communications Conference. DOI= http://dx.doi.org/10.1109/GLOCOM.2016.7842016

5. Changsheng You, Kaibin Huang, Hyukjin Chae, and Byoung-Hoon Kim. 2016. Energy-efficient resource allocation for mobile-edge computation offloading. IEEE Transactions on Wireless Communications, 16, 3, 1397--1411.

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