Incentivizing self-capping to increase cloud utilization

Mohammad Shahrad, Cristian Klein, Liang Zheng, Mung Chiang, Erik Elmroth, David Wentzlaff

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

17 Scopus citations


Cloud Infrastructure as a Service (IaaS) providers continually seek higher resource utilization to better amortize capital costs. Higher utilization not only can enable higher proit for IaaS providers but also provides a mechanism to raise energy eiciency; therefore creating greener cloud services. Unfortunately, achieving high utilization is diicult mainly due to infrastructure providers needing to maintain spare capacity to service demand luctuations. Graceful degradation is a self-adaptation technique originally designed for constructing robust services that survive resource shortages. Previous work has shown that graceful degradation can also be used to improve resource utilization in the cloud by absorbing demand luctuations and reducing spare capacity. In this work, we build a system and pricing model that enables infrastructure providers to incentivize their tenants to use graceful degradation. By using graceful degradation with an appropriate pricing model, the infrastructure provider can realize higher resource utilization while simultaneously, its tenants can increase their proit. Our proposed solution is based on a hybrid model which guarantees both reserved and peak on-demand capacities over lexible periods. It also includes a global dynamic price pair for capacity which remains uniform during each tenant's Service Level Agreement (SLA) term. We evaluate our scheme using simulations based on real-world traces and also implement a prototype using RUBiS on the Xen hypervisor as an end-to-end demonstration. Our analysis shows that the proposed scheme never hurts a tenant's net proit, but can improve it by as much as 93%. Simultaneously, it can also improve the efective utilization of contracts from 42% to as high as 99%.

Original languageEnglish (US)
Title of host publicationSoCC 2017 - Proceedings of the 2017 Symposium on Cloud Computing
PublisherAssociation for Computing Machinery, Inc
Number of pages14
ISBN (Electronic)9781450350280
StatePublished - Sep 24 2017
Event2017 Symposium on Cloud Computing, SoCC 2017 - Santa Clara, United States
Duration: Sep 24 2017Sep 27 2017

Publication series

NameSoCC 2017 - Proceedings of the 2017 Symposium on Cloud Computing


Other2017 Symposium on Cloud Computing, SoCC 2017
Country/TerritoryUnited States
CitySanta Clara

All Science Journal Classification (ASJC) codes

  • Computational Theory and Mathematics
  • Theoretical Computer Science


  • Cloud computing
  • Dynamic pricing
  • Economic incentives
  • IaaS
  • Pricing model
  • Resource management
  • SLA
  • Utilization


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