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DepCon: Achieving Network SLO for High Performance Clouds

Authors
Kim, E.Lee, K.Yoo, C.
Issue Date
2022
Publisher
Springer Science and Business Media Deutschland GmbH
Citation
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v.13098 LNCS, pp.339 - 351
Indexed
SCOPUS
Journal Title
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume
13098 LNCS
Start Page
339
End Page
351
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/146985
DOI
10.1007/978-3-031-06156-1_27
ISSN
0302-9743
Abstract
As containers run in a distributed manner in clouds, it is important to satisfy network service level objectives (SLOs) for containers. In addition, it has been known that containers utilize more CPU resources for network processing than native processes because of the long networking stack of containers. Thus, for achieving network SLOs, containers require sufficient CPU resources as well as network resources, which we call inter-resource dependency. However, existing cloud schedulers have limitations in that they do not take CPU into account for the network SLO. This paper proposes DepCon that controls CPU resources for containers to satisfy network SLOs. DepCon consists of DepCon scheduler that works in the cloud-level and DepCon agent at each node. We implement DepCon in the most popular container orchestration platform, Kubernetes. Our evaluation results show that DepCon reduces the network performance variance by 20 times while improving the network throughput by 40%. In addition, DepCon reduces the scheduling overhead by 20 times compared to the representative multi-resource scheduling technique like DRF. © 2022, Springer Nature Switzerland AG.
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