Revenue driven resource allocation for virtualized data centers

Sajib Kundu, Raju Rangaswami, Ming Zhao, Ajay Gulati, Kaushik Dutta

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

7 Scopus citations

Abstract

The increasing VM density in cloud hosting services makes careful management of physical resources such as CPU, memory, and I/O bandwidth within individual virtualized servers a priority. To maximize cost-efficiency, resource management needs to be coupled with the revenue generating mechanisms of cloud hosting: the service level agreements (SLAs) of hosted client applications. In this paper, we develop a server resource management framework that reduces data center resource management complexity substantially. Our solution implements revenue-driven dynamic resource allocation which continuously steers the resource distribution across hosted VMs within a server such as to maximize the SLA-generated revenue from the server. Our experimental evaluation for a VMware ESX hyper visor highlights the importance of both resource isolation and resource sharing across VMs. The empirical data shows a 7%-54% increase in total revenue generated for a mix of 10-25 VMs hosting either similar or diverse workloads when compared to using the currently available resource distribution mechanisms in ESX.

Original languageEnglish (US)
Title of host publicationProceedings - IEEE International Conference on Autonomic Computing, ICAC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages197-206
Number of pages10
ISBN (Print)9781467369701
DOIs
StatePublished - Sep 14 2015
Externally publishedYes
Event12th IEEE International Conference on Autonomic Computing, ICAC 2015 - Grenoble, France
Duration: Jul 7 2015Jul 10 2015

Other

Other12th IEEE International Conference on Autonomic Computing, ICAC 2015
CountryFrance
CityGrenoble
Period7/7/157/10/15

Keywords

  • Cloud computing
  • Data centers
  • Resource allocation
  • SLA
  • Virtualization

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Software
  • Control and Systems Engineering

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  • Cite this

    Kundu, S., Rangaswami, R., Zhao, M., Gulati, A., & Dutta, K. (2015). Revenue driven resource allocation for virtualized data centers. In Proceedings - IEEE International Conference on Autonomic Computing, ICAC 2015 (pp. 197-206). [7266964] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICAC.2015.40