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An effective grouping method for unstructured data based on Swift

  • Harbin Institute of Technology Weihai

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

Abstract

Unstructured data is one of the most prominent buzzwords of this era, and from the business to the personal computer, unstructured data is ubiquitous and growing exponentially, managing these data and improving the access performance of these unstructured data is Critical. This paper is based on Swift which is the object storage service of open source cloud computing platform OpenStack, with the help of object storage framework, the use of grouping-based machine learning technology and the corresponding prefetching cache strategy to improve the access performance of unstructured data. Experimentally verify the performance improvement of the proposed method with respect to memory consumption, cache hit ratio, and latency of requests. Experimental results show that the proposed method can effectively reduce the cache consumption and request delay time and can greatly improve the cache hit rate.

Original languageEnglish
Title of host publicationICCDE 2018 - International Conference on Computing and Data Engineering
PublisherAssociation for Computing Machinery
Pages34-38
Number of pages5
ISBN (Print)9781450363938
DOIs
StatePublished - 4 May 2018
Externally publishedYes
Event2018 International Conference on Computing and Data Engineering, ICCDE 2018 - Shanghai, China
Duration: 4 May 20186 May 2018

Publication series

NameACM International Conference Proceeding Series
VolumePart F137704

Conference

Conference2018 International Conference on Computing and Data Engineering, ICCDE 2018
Country/TerritoryChina
CityShanghai
Period4/05/186/05/18

Keywords

  • Data prefetching
  • Grouping
  • Swift
  • Unstructured data

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