Burstable Instances for Clouds: Performance Modeling, Equilibrium Analysis, and Revenue Maximization

Yuxuan Jiang, Mohammad Shahrad, David Wentzlaff, Danny H.K. Tsang, Carlee Joe-Wong

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Scopus citations


Leading cloud providers recently introduced a new instance type named burstable instances to better match the time-varying workloads of tenants and further reduce their costs. In the research community, however, little has been done to understand burstable instances from a theoretical perspective. This paper presents the first unified framework to model, analyze, and optimize the operation of burstable instances. Specifically, we model the resource provisioning of burstable instances in different service classes, identify key performance metrics, and derive the performance given the resource provisioning decisions. We then characterize the equilibrium behind tenants' responses to the prices offered for different burstable instance service classes, taking into account the impact of tenants' actions on the performance achieved by each service class. In addition, we investigate how a cloud provider can leverage the knowledge of this equilibrium to find the prices that maximize its total revenue. Finally, we validate our framework on real traces and demonstrate its usage to price a public cloud.

Original languageEnglish (US)
Title of host publicationINFOCOM 2019 - IEEE Conference on Computer Communications
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages9
ISBN (Electronic)9781728105154
StatePublished - Apr 2019
Event2019 IEEE Conference on Computer Communications, INFOCOM 2019 - Paris, France
Duration: Apr 29 2019May 2 2019

Publication series

NameProceedings - IEEE INFOCOM
ISSN (Print)0743-166X


Conference2019 IEEE Conference on Computer Communications, INFOCOM 2019

All Science Journal Classification (ASJC) codes

  • General Computer Science
  • Electrical and Electronic Engineering


  • burstable instances
  • cloud
  • equilibrium
  • revenue maximization


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