A heuristics-based VM allocation mechanism for cloud data centers

Jing V. Wang, Nuwan Ganganath, Chi Tsun Cheng, Chi Kong Tse

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

2 Citations (Scopus)

Abstract

Live migration, which allows virtual machines (VMs) to move across distinct physical hosts, is widely adopted for realizing energy saving and load balancing in modern Cloud data centers. However, putting VMs with high correlations on their CPU utilization patterns onto the same host is very likely to trigger overloading incidents and commit Service Level Agreements (SLA) violations, even when the host has not yet reached its critical limits. To avoid such SLA violations and to maintain a low energy consumption, this work proposes a heuristics-based VM allocation mechanism. Under the proposed mechanism, VMs showing high CPU utilization correlations to other co-located peers and hosts with extreme utilization values are both assigned with high heuristic values. VMs with high heuristic values are therefore less preferred to be co-located onto a host that has a high heuristic value. Performance of the proposed mechanism was evaluated using CloudSim with real-world workload data. Simulation results show that when comparing with other existing mechanisms, the proposed idea can further reduce both energy consumption and SLA violations.
Original languageEnglish
Title of host publicationIEEE International Symposium on Circuits and Systems
Subtitle of host publicationFrom Dreams to Innovation, ISCAS 2017 - Conference Proceedings
PublisherIEEE
ISBN (Electronic)9781467368520
DOIs
Publication statusPublished - 25 Sep 2017
Event50th IEEE International Symposium on Circuits and Systems, ISCAS 2017 - Baltimore, United States
Duration: 28 May 201731 May 2017

Conference

Conference50th IEEE International Symposium on Circuits and Systems, ISCAS 2017
CountryUnited States
CityBaltimore
Period28/05/1731/05/17

Keywords

  • cloud computing
  • CPU utilization
  • heuristics
  • multiple correlation
  • VM allocation

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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