DeepRLB: A deep reinforcement learning‐based load balancing in data center networks

Author:

Rikhtegar Negar1,Bushehrian Omid1ORCID,Keshtgari Manijeh1

Affiliation:

1. Department of Computer Engineering and Information Technology Shiraz University of Technology Shiraz Iran

Publisher

Wiley

Subject

Electrical and Electronic Engineering,Computer Networks and Communications

Reference52 articles.

1. Cisco Global Cloud Index: forecast and methodology 2016‐2021. (n.d.).https://www.readkong.com/page/cisco-global-cloud-index-forecast-and-methodology-4248491?p=1.Accessed July 27 2020.

2. BensonT AnandA AkellaA ZhangM.MicroTE: fine grained traffic engineering for data centers. In: Proceedings of the Seventh conference on emerging Networking Experiments and Technologies;2011:1‐12.https://doi.org/10.1145/2079296.2079304

3. BensonT AkellaA MaltzDA.Network traffic characteristics of data centers in the wild. In: Proceedings of the 10th Annual Conference on Internet Measurement – IMC'10.2010:267‐280.https://doi.org/10.1145/1879141.1879175

4. HellerB SeetharamanS MahadevanP et al.ElasticTree: saving energy in data center networks. In: Proceedings of the 7th USENIX Conference on Networked Systems Design and Implementation.2010:249‐264.

5. BensonT AnandA AkellaA ZhangM.The case for fine‐grained traffic engineering in data centers. In:Proceedings of the 2010 Internet Network Management Conference on Research on Enterprise Networking‐INM/WREN'10.2010.

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