Experience-based Computation Offloading by Deep Reinforcement Learning for Multi-access Edge Computing Network

Author:

Li Kexin1,Wang Xingwei1,Yi Bo1

Affiliation:

1. College of Computer Science and Engineering, Northeastern University, China

Funder

National Key R&D Program of China

National Natural Science Foundation of China

Liaoning Revitalization Talents Program

Publisher

ACM

Reference26 articles.

1. S. Bi and Yja Zhang . 2018 . An ADMM Based Method for Computation Rate Maximization in Wireless Powered Mobile-Edge Computing Networks. In 2018 IEEE International Conference on Communications (ICC). S. Bi and Yja Zhang. 2018. An ADMM Based Method for Computation Rate Maximization in Wireless Powered Mobile-Edge Computing Networks. In 2018 IEEE International Conference on Communications (ICC).

2. Experience Selection in Deep Reinforcement Learning for Control;Bruin D.;Journal of Machine Learning Research,2018

3. [ 3 ] Xianfu Chen Honggang Zhang Celimuge Wu Shiwen Mao Yusheng Ji and Medhi Bennis.[n.d.]. ([n. d.]). [3] Xianfu Chen Honggang Zhang Celimuge Wu Shiwen Mao Yusheng Ji and Medhi Bennis.[n.d.]. ([n. d.]).

4. Boosted Metaheuristic Algorithms for QoE-Aware Server Selection in Multiplayer Cloud Gaming

5. Computation Offloading and Resource Allocation in Mixed Fog/Cloud Computing Systems With Min-Max Fairness Guarantee

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