Townend, P, Clement, S, Burdett, D et al. (4 more authors) (2019) Invited Paper: Improving Data Center Efficiency Through Holistic Scheduling In Kubernetes. In: Proceedings of the 2019 IEEE International Conference on Service-Oriented System Engineering (SOSE). 2019 IEEE International Conference on Service-Oriented System Engineering (SOSE), 04-09 Apr 2019, San Francisco East Bay, CA, USA. IEEE , pp. 156-166. ISBN 978-1-7281-1443-9
Abstract
Data centers are the infrastructure that underpins modern distributed service-oriented systems. They are complex systems-of-systems, with many interacting elements, that consume vast amounts of power. Demand for such facilities is growing rapidly, leading to significant global environmental impact. The data center industry has conducted much research into efficiency improvements, but this has mostly been at the physical infrastructure level. Research into software-based solutions for improving efficiency is greatly needed. However, most current research does not take a holistic view of the data center that considers virtual and physical infrastructures as well as business process. This is crucial if a solution is to be applied in a realistic setting. This paper describes the complex, system-of-systems nature of data centers, and discusses the service models used in the industry. We describe a holistic scheduling system that replaces the default scheduler in the Kubernetes container system, taking into account both software and hardware models. We discuss the initial results of deploying this scheme in a real data center, where power consumption reductions of 10-20% were observed. We show that by introducing hardware modelling into a software-based solution, an intelligent scheduler can make significant improvements in data center efficiency. We conclude by looking at some of the future work that needs to be performed in this area.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Keywords: | Data centers; Servers; Software; Industries; Cooling; Hardware; Data models |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 21 Oct 2020 14:42 |
Last Modified: | 25 Jun 2023 22:28 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/sose.2019.00030 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:166899 |