Performance models of storage contention in cloud environments

Stephan Kraft*, Giuliano Casale, Diwakar Krishnamurthy, Des Greer, Peter Kilpatrick

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

13 Citations (Scopus)
364 Downloads (Pure)


We propose simple models to predict the performance degradation of disk requests due to storage device contention in consolidated virtualized environments. 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 server. We first propose a trace-driven approach that evaluates a queueing network with fair share scheduling using simulation. The model parameters consider Virtual Machine Monitor level disk access optimizations and rely on a calibration technique. We further present a measurement-based approach that allows a distinct characterization of read/write performance attributes. In particular, we define simple linear prediction models for I/O request mean response times, throughputs and read/write mixes, as well as a simulation model for predicting response time distributions. We found our models to be effective in predicting such quantities across a range of synthetic and emulated application workloads. 

Original languageEnglish
Pages (from-to)681-704
Number of pages24
JournalSoftware and Systems Modeling
Issue number4
Early online date02 Mar 2012
Publication statusPublished - 01 Oct 2013


  • Performance modeling
  • Virtualization
  • Storage

ASJC Scopus subject areas

  • Modelling and Simulation
  • Software


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