research-article

Tableau: a high-throughput and predictable VM scheduler for high-density workloads

Authors:

Arpan Gujarati,

Björn B. BrandenburgAuthors Info & Claims

EuroSys '18: Proceedings of the Thirteenth EuroSys Conference

Article No.: 28, Pages 1 - 16

https://doi.org/10.1145/3190508.3190557

Published: 23 April 2018 Publication History

Abstract

In the increasingly competitive public-cloud marketplace, improving the efficiency of data centers is a major concern. One way to improve efficiency is to consolidate as many VMs onto as few physical cores as possible, provided that performance expectations are not violated. However, as a prerequisite for increased VM densities, the hypervisor's VM scheduler must allocate processor time efficiently and in a timely fashion. As we show in this paper, contemporary VM schedulers leave substantial room for improvements in both regards when facing challenging high-VM-density workloads that frequently trigger the VM scheduler. As root causes, we identify (i) high runtime overheads and (ii) unpredictable scheduling heuristics. To better support high VM densities, we propose Tableau, a VM scheduler that guarantees a minimum processor share and a maximum bound on scheduling delay for every VM in the system. Tableau combines a low-overhead, core-local, table-driven dispatcher with a fast on-demand table-generation procedure (triggered on VM creation/teardown) that employs scheduling techniques typically used in hard real-time systems. In an evaluation of Tableau and three current Xen schedulers on a 16-core Intel Xeon machine, Tableau is shown to improve tail latency (e.g., a 17X reduction in maximum ping latency compared to Credit) and throughput (e.g., 1.6X peak web server throughput compared to RTDS when serving 1 KiB files with a 100 ms SLA).

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Cited By

Yarlagadda HPampana SNerella CVemuri J(2024)A Novel Implementation of Tableau Software for the Visualisation of Seismic Data from Himalayan RegionAdvances in Risk and Reliability Modelling and Assessment10.1007/978-981-97-3087-2_9(95-105)Online publication date: 1-Jun-2024
https://doi.org/10.1007/978-981-97-3087-2_9
Wang YYu JYu Z(2023)Resource scheduling techniques in cloud from a view of coordination: a holistic survey从协同视角论云资源调度技术：综述Frontiers of Information Technology & Electronic Engineering10.1631/FITEE.210029824:1(1-40)Online publication date: 23-Jan-2023
https://doi.org/10.1631/FITEE.2100298
Subrata TYanto DRizky AHikam IJuan Situmorang H(2022)Implementation of the Tableau Application to Determine Earthquake Prone Areas with Geolocation Features2022 IEEE Creative Communication and Innovative Technology (ICCIT)10.1109/ICCIT55355.2022.10119061(1-6)Online publication date: 22-Nov-2022
https://doi.org/10.1109/ICCIT55355.2022.10119061
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Index Terms

Tableau: a high-throughput and predictable VM scheduler for high-density workloads
1. Computer systems organization
  1. Architectures
    1. Distributed architectures
      1. Cloud computing
  2. Real-time systems
2. Software and its engineering
  1. Software organization and properties
    1. Contextual software domains
      1. Operating systems
        Process management
        Scheduling
      2. Software infrastructure
        Virtual machines
    2. Software functional properties
      1. Correctness
        Real-time schedulability

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cover image ACM Conferences

EuroSys '18: Proceedings of the Thirteenth EuroSys Conference

April 2018

631 pages

ISBN:9781450355841

DOI:10.1145/3190508

General Chair:
Rui Oliveira,
Program Chairs:
Pascal Felber,
Y. Charlie Hu

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Published: 23 April 2018

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EuroSys '18: Thirteenth EuroSys Conference 2018

April 23 - 26, 2018

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EuroSys '18 Paper Acceptance Rate 43 of 262 submissions, 16%;

Overall Acceptance Rate 241 of 1,308 submissions, 18%

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https://doi.org/10.1007/978-981-97-3087-2_9
Wang YYu JYu Z(2023)Resource scheduling techniques in cloud from a view of coordination: a holistic survey从协同视角论云资源调度技术：综述Frontiers of Information Technology & Electronic Engineering10.1631/FITEE.210029824:1(1-40)Online publication date: 23-Jan-2023
https://doi.org/10.1631/FITEE.2100298
Subrata TYanto DRizky AHikam IJuan Situmorang H(2022)Implementation of the Tableau Application to Determine Earthquake Prone Areas with Geolocation Features2022 IEEE Creative Communication and Innovative Technology (ICCIT)10.1109/ICCIT55355.2022.10119061(1-6)Online publication date: 22-Nov-2022
https://doi.org/10.1109/ICCIT55355.2022.10119061
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