Cloud bursting approach based on predicting requests for business-critical web systems

Yukio Ogawa, Go Hasegawa, Masayuki Murata

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

6 Citations (Scopus)

Abstract

Cloud bursting temporarily expands the capacity of cloud-based service hosted in a private data center by renting public data center capacity when the demand for capacity spikes. This paper presents a cloud bursting approach based on long- and short-term predictions of requests to a business-critical web system to determine the optimal resources of the system deployed over private and public data centers. In a private data center, a dedicated pool of virtual machines (VMs) is assigned to the web system on the basis of one-week predictions. Moreover, in both private and public data centers, VMs are activated on the basis of one-hour predictions. We formulated a problem that includes the total cost and response time constraints and conducted numerical simulations. The results indicate that our approach is tolerant of prediction errors. Even if the website receives bursty requests and one-hour predictions include a mean absolute percentage error (MAPE) of 0.2, the total cost decreases to a half the current cost while 95% of response time is kept below 0.15 s.

Original languageEnglish
Title of host publication2017 International Conference on Computing, Networking and Communications, ICNC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages437-441
Number of pages5
ISBN (Electronic)9781509045884
DOIs
Publication statusPublished - 2017 Mar 10
Externally publishedYes
Event2017 International Conference on Computing, Networking and Communications, ICNC 2017 - Silicon Valley, United States
Duration: 2017 Jan 262017 Jan 29

Publication series

Name2017 International Conference on Computing, Networking and Communications, ICNC 2017

Other

Other2017 International Conference on Computing, Networking and Communications, ICNC 2017
CountryUnited States
CitySilicon Valley
Period17/1/2617/1/29

Keywords

  • cloud bursting
  • hybrid cloud
  • request prediction

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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