Precise VM placement algorithm supported by data analytic service

Dapeng Dong, John Herbert

Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review

1 Citation (Scopus)

Abstract

The popularity and commercial use of cloud computing has prompted an increased concern among cloud service providers for both energy efficiency and quality of service. One of the key techniques used for the efficient use of cloud server resources is virtual machine placement. This work introduces a precise VM placement algorithm for power conservation and SLA violation prevention. The mathematical model of the algorithm is supported by a sophisticated data analytic system implemented as a service. The precision of the algorithm is achieved by allowing each individual VM to build, on demand, its own data model over an appropriate time horizon. Thus the data model can reflect the characteristics of resource usage of the VM accurately. The algorithm can communicate synchronously or asynchronously with the data analytic service which is deployed as a cloud-based solution. In the experiments, several advanced data modelling and use forecasting techniques were evaluated. Results from simulation-based experiments show that the VM placement algorithm (supported by the data analytic service) can effectively reduce power consumption, the number of VM migrations, and prevent SLA violation; it also compares favourably with other heuristic algorithms.

Original languageEnglish
Title of host publicationCLOSER 2013 - Proceedings of the 3rd International Conference on Cloud Computing and Services Science
Pages463-468
Number of pages6
Publication statusPublished - 2013
Externally publishedYes
Event3rd International Conference on Cloud Computing and Services Science, CLOSER 2013 - Aachen, Germany
Duration: 8 May 201310 May 2013

Publication series

NameCLOSER 2013 - Proceedings of the 3rd International Conference on Cloud Computing and Services Science

Conference

Conference3rd International Conference on Cloud Computing and Services Science, CLOSER 2013
Country/TerritoryGermany
CityAachen
Period8/05/1310/05/13

Keywords

  • Cloud computing
  • Decision support
  • Forecast
  • VM placement

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