Introspection of Virtual Machine Memory Resource in the Virtualized Systems

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

3 Scopus citations

Abstract

Nowadays, data center and cloud servers have commonly adopted virtualization technologies to consolidate multiple servers into a physical one. It is because cloud service providers can achieve low server maintenance cost by improving resource utilization and reducing power consumption through server consolidation with virtualization technologies. However, unlike the physical system resources such as CPU and storage which can be flexibly utilized and shared by using time-based schedulers, memory resource is not easy for flexible utilization and sharing in that the memory size of each virtual machine is fixed by initial configuration. For this reason, sufficient understanding on memory resource usage of each virtual machine is essential in analyzing the existing memory management techniques such as memory ballooning and virtual machine migration. In this paper, we introduce a novel virtual machine memory monitoring tool, called SELF-e, which is developed for tracing the page accesses of each virtual machine in real-time and collecting necessary information on shared pages. Experimental results show that SELF-e efficiently announces the information on classified pages without significant performance degradation.

Original languageEnglish
Title of host publication2019 IEEE International Conference on Big Data and Smart Computing, BigComp 2019 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538677896
DOIs
StatePublished - 1 Apr 2019
Event2019 IEEE International Conference on Big Data and Smart Computing, BigComp 2019 - Kyoto, Japan
Duration: 27 Feb 20192 Mar 2019

Publication series

Name2019 IEEE International Conference on Big Data and Smart Computing, BigComp 2019 - Proceedings

Conference

Conference2019 IEEE International Conference on Big Data and Smart Computing, BigComp 2019
Country/TerritoryJapan
CityKyoto
Period27/02/192/03/19

Keywords

  • content-based memory sharing
  • virtual machine migration
  • virtual-machine monitoring tool

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