Cost-aware automatic virtual machine scaling in fine granularity for cloud applications

He Zhao, Chenglei Peng, Yao Yu, Yu Zhou, Ziqiang Wang, Sidan Du

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

1 Citation (Scopus)

Abstract

It is a tendency for enterprises to deploy their applications on Infrastructure as a Service (IaaS) platforms. Many latest IaaS service providers offer Virtual Machine (VM) instances with various capacities and prices by the minute. In this paper, based on the observation that the workload of nowaday applications fluctuates frequently, we propose a costaware automatic VM scaling method of fine granularity to satisfy the Service Level Agreement (SLA) and minimize the rent of VMs down to the minute. In the environment with sporadic and sharp swings of workload, our approach acts quickly to get suitable VM scaling scheme to stabilize the response time, reduce the SLA violations and save the rent of VM usage.

Original languageEnglish
Title of host publicationProceedings - 2013 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC 2013
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages109-116
Number of pages8
ISBN (Print)9780768551067
DOIs
Publication statusPublished - 1 Jan 2013
Event2013 5th International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC 2013 - Beijing, China
Duration: 10 Oct 201312 Oct 2013

Publication series

NameProceedings - 2013 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC 2013

Conference

Conference2013 5th International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC 2013
CountryChina
CityBeijing
Period10/10/1312/10/13

Keywords

  • Cloud computing
  • Costaware criteria
  • Virtual machine scaling

Cite this

Zhao, H., Peng, C., Yu, Y., Zhou, Y., Wang, Z., & Du, S. (2013). Cost-aware automatic virtual machine scaling in fine granularity for cloud applications. In Proceedings - 2013 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC 2013 (pp. 109-116). [6685667] (Proceedings - 2013 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC 2013). IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/CyberC.2013.26