Multi-Agent Reinforcement Learning for Network Load Balancing in Data Center-Reference-Cited by-同舟云学术

Multi-Agent Reinforcement Learning for Network Load Balancing in Data Center

Published:2022-10-17 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 31st ACM International Conference on Information & Knowledge Management
language:
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Author:

Yao Zhiyuan¹,Ding Zihan²,Clausen Thomas³

Affiliation:

1. École Polytechnique & Cisco Systems, Paris, UNK, France

2. Princeton University, Princeton, NJ, USA

3. École Polytechnique, Paris, UNK, France

Funder

This work is, in part, supported by the Cisco endowed ðInternet Technologies and Engineeringð chaire at École Polytechnique.

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3511808.3557133

Reference32 articles.

1. Ashkan Aghdai , Cing-Yu Chu , Yang Xu , David H Dai , Jun Xu , and H Jonathan Chao . 2018 a. Spotlight: Scalable Transport Layer Load Balancing for Data Center Networks. arXiv preprint arXiv:1806.08455 (2018). Ashkan Aghdai, Cing-Yu Chu, Yang Xu, David H Dai, Jun Xu, and H Jonathan Chao. 2018a. Spotlight: Scalable Transport Layer Load Balancing for Data Center Networks. arXiv preprint arXiv:1806.08455 (2018).

2. Ashkan Aghdai , Michael I-C Wang , Yang Xu, Charles H-P Wen, and H Jonathan Chao. 2018 b. In-network Congestion-aware Load Balancing at Transport Layer . arXiv preprint arXiv:1811.09731 (2018). Ashkan Aghdai, Michael I-C Wang, Yang Xu, Charles H-P Wen, and H Jonathan Chao. 2018b. In-network Congestion-aware Load Balancing at Transport Layer. arXiv preprint arXiv:1811.09731 (2018).

3. Deep Reinforcement Learning-based CIO and Energy Control for LTE Mobility Load Balancing

4. AuTO

5. Petros Christodoulou . 2019. Soft actor-critic for discrete action settings. arXiv preprint arXiv:1910.07207 ( 2019 ). Petros Christodoulou. 2019. Soft actor-critic for discrete action settings. arXiv preprint arXiv:1910.07207 (2019).

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