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

1 Scopus citations

Abstract

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.
Pages1576-1584
Number of pages9
ISBN (Electronic)9781728105154
DOIs
StatePublished - Apr 2019
Event2019 IEEE Conference on Computer Communications, INFOCOM 2019 - Paris, France
Duration: Apr 29 2019May 2 2019

Publication series

NameProceedings - IEEE INFOCOM
Volume2019-April
ISSN (Print)0743-166X

Conference

Conference2019 IEEE Conference on Computer Communications, INFOCOM 2019
CountryFrance
CityParis
Period4/29/195/2/19

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Electrical and Electronic Engineering

Keywords

  • burstable instances
  • cloud
  • equilibrium
  • revenue maximization

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    Jiang, Y., Shahrad, M., Wentzlaff, D., Tsang, D. H. K., & Joe-Wong, C. (2019). Burstable Instances for Clouds: Performance Modeling, Equilibrium Analysis, and Revenue Maximization. In INFOCOM 2019 - IEEE Conference on Computer Communications (pp. 1576-1584). [8737634] (Proceedings - IEEE INFOCOM; Vol. 2019-April). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/INFOCOM.2019.8737634