Transaction-aware data cluster allocation scheme for Qcow2-based virtual disks

Minho Lee, Young Ik Eom

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

5 Scopus citations

Abstract

Recently, virtualization has become one of the backbone technologies for constructing data centers and cloud systems because it facilitates server consolidation through its attractive features. One major benefit of the virtualization technology is to support the physical server in concurrently running multiple VMs by logically partitioning the system resources into multiple ones. In constructing a virtualized system with multiple VMs, the qcow2 format is widely used as a virtual disk layout due to its storage space efficiency. However, the qcow2-based virtual disk has a critical drawback with respect to I/O performance. With the qcow2 format, excessive file sync operations are called in the process of data cluster allocation. In this paper, we introduce an efficient data cluster allocation scheme for the qcow2-based virtual disk to mitigate the performance overhead caused by the excessive file sync calls. For this, we adopt transactional support to the qcow2-based virtual disk and propose a new file sync operation, called gsync, which flushes the modified metadata in a bundle. Experimental results show that our scheme reduces the number of sync operations by up to 50.6% and improves I/O performance by up to 26.1%, compared with the conventional scheme.

Original languageEnglish
Title of host publicationProceedings - 2020 IEEE International Conference on Big Data and Smart Computing, BigComp 2020
EditorsWookey Lee, Luonan Chen, Yang-Sae Moon, Julien Bourgeois, Mehdi Bennis, Yu-Feng Li, Young-Guk Ha, Hyuk-Yoon Kwon, Alfredo Cuzzocrea
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages385-388
Number of pages4
ISBN (Electronic)9781728160344
DOIs
StatePublished - Feb 2020
Event2020 IEEE International Conference on Big Data and Smart Computing, BigComp 2020 - Busan, Korea, Republic of
Duration: 19 Feb 202022 Feb 2020

Publication series

NameProceedings - 2020 IEEE International Conference on Big Data and Smart Computing, BigComp 2020

Conference

Conference2020 IEEE International Conference on Big Data and Smart Computing, BigComp 2020
Country/TerritoryKorea, Republic of
CityBusan
Period19/02/2022/02/20

Keywords

  • Data cluster allocation
  • Qcow2 format
  • Sync operation
  • Transactional support
  • Virtualization

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