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HSPP: Load-Balanced and Low-Latency File Partition and Placement Strategy on Distributed Heterogeneous Storage with Erasure Coding

  • Beihang University

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

Abstract

To speedup the accesses to massive amount of data, heterogeneous architecture has been widely adopted in the mainstream storage system. In such systems, load imbalance and scheduler overhead are the primary factors that slow down the I/O performance. In this paper, we propose an effective file scheduling strategy HSPP that includes statistic based file classification, partition with erasure coding and adaptive data placement to optimize load balance and read latency on the distributed heterogeneous storage system. The experiment results show that HSPP is superior than existing strategies in terms of load balance, read latency, and scheduling overhead.

Original languageEnglish
Title of host publicationAlgorithms and Architectures for Parallel Processing - 19th International Conference, ICA3PP 2019, Proceedings
EditorsSheng Wen, Albert Zomaya, Laurence T. Yang
PublisherSpringer
Pages200-214
Number of pages15
ISBN (Print)9783030389604
DOIs
StatePublished - 2020
Event19th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2019 - Melbourne, Australia
Duration: 9 Dec 201911 Dec 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11945 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference19th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2019
Country/TerritoryAustralia
CityMelbourne
Period9/12/1911/12/19

Keywords

  • Data partition and placement
  • Erasure coding
  • Heterogeneous storage

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