IO Performance Prediction in Consolidated Virtualized Environments

Stephen Kraft, Giuliano Casale, Diwakar Krishnamurthy, Des Greer, Peter Kilpatrick

Research output: Chapter in Book/Report/Conference proceedingOther chapter contribution

20 Citations (Scopus)

Abstract

We propose a trace-driven approach to predict the performance degradation of disk request response times due to storage device contention in consolidated virtualized environments. Our performance model evaluates a queueing network with fair share scheduling using trace-driven simulation. The model parameters can be deduced from measurements obtained inside Virtual Machines (VMs) from a system where a single VM accesses a remote storage server. The parameterized model can then be used to predict the effect of storage contention when multiple VMs are consolidated on the same virtualized server. The model parameter estimation relies on a search technique that tries to estimate the splitting and merging of blocks at the the Virtual Machine Monitor (VMM) level in the case of multiple competing VMs. Simulation experiments based on traces of the Postmark and FFSB disk benchmarks show that our model is able to accurately predict the impact of workload consolidation on VM disk IO response times.
Original languageEnglish
Title of host publicationICPE'11 - Proceedings of the 2nd Joint WOSP/SIPEW International Conference on Performance Engineering
Place of PublicationNew York
PublisherAssociation for Computing Machinery
Pages295-306
Number of pages12
ISBN (Print)978-1-4503-0519-8
DOIs
Publication statusPublished - 2011

Keywords

  • Queueing Networks
  • Simulation
  • Virtualization
  • Storage Contention

Fingerprint

Dive into the research topics of 'IO Performance Prediction in Consolidated Virtualized Environments'. Together they form a unique fingerprint.

Cite this