HotDataTrap: A sampling-based hot data identification scheme for flash memory

Dongchul Park, Biplob Debnath, Youngjin Nam, David H Du, Youngkyun Kim, Youngchul Kim

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

13 Scopus citations

Abstract

Hot data identification is an issue of paramount importance in flash-based storage devices since it has a great impact on their overall performance as well as retains a big potential to be applicable to many other fields. However, it has been least investigated. HotDataTrap is a novel on-line hot data identification scheme adopting a sampling mechanism. This sampling-based algorithm enables HotDataTrap to early discard some of the cold items so that it can reduce runtime overheads and a waste of memory spaces. Moreover, its two-level hierarchical hash indexing scheme helps HotDataTrap directly look up a requested item in the cache and save a memory space further by exploiting spatial localities. Both our sampling approach and hierarchical hash indexing scheme empower HotDataTrap to precisely and efficiently identify hot data with a very limited memory space. Our extensive experiments with various realistic workloads demonstrate that our HotDataTrap outperforms the state-of-the-art scheme by an average of 335% and and our two-level hash indexing scheme considerably improves further HotDataTrap performance up to 50.8%.

Original languageEnglish (US)
Title of host publication27th Annual ACM Symposium on Applied Computing, SAC 2012
Pages1610-1617
Number of pages8
DOIs
StatePublished - 2012
Event27th Annual ACM Symposium on Applied Computing, SAC 2012 - Trento, Italy
Duration: Mar 26 2012Mar 30 2012

Publication series

NameProceedings of the ACM Symposium on Applied Computing

Other

Other27th Annual ACM Symposium on Applied Computing, SAC 2012
CountryItaly
CityTrento
Period3/26/123/30/12

Keywords

  • HotDataTrap
  • SSD
  • flash memory
  • hot data identification

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