MetisRL: A Reinforcement Learning Approach for Dynamic Routing in Data Center Networks

Gao, Y.; Gao, Xiaofeng; Chen, Guihai

doi:10.1007/978-3-031-00126-0_44

Search citation statements

Order By: Relevance

Paper Sections

Select...

Traffic Scheduling Based On Intelligent Algorithms1

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

(1 citation statement)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, it may necessitate a complex coordination mechanism to ensure effective cooperation among the agents. Gao et al [31] captured historical traffic matrices and monitored link utilization through an SDN controller. RL components are then utilized for dynamic prediction, and traffic scheduling decisions are output accordingly.…”

Section: Traffic Scheduling Based On Intelligent Algorithmsmentioning

confidence: 99%

Review of Load Balancing Mechanisms in SDN-Based Data Centers

Du,

Cui,

Tang

et al. 2024

JCC

View full text Add to dashboard Cite

With the continuous expansion of the data center network scale, changing network requirements, and increasing pressure on network bandwidth, the traditional network architecture can no longer meet people's needs. The development of software defined networks has brought new opportunities and challenges to future networks. The data and control separation characteristics of SDN improve the performance of the entire network. Researchers have integrated SDN architecture into data centers to improve network resource utilization and performance. This paper first introduces the basic concepts of SDN and data center networks. Then it discusses SDN-based load balancing mechanisms for data centers from different perspectives. Finally, it summarizes and looks forward to the study on SDN-based load balancing mechanisms and its development trend.

show abstract

Section: Traffic Scheduling Based On Intelligent Algorithmsmentioning

confidence: 99%