Provenance-based prediction scheme for object storage system in HPC

Dong Dai, Yong Chen, Dries Kimpe, Rob Ross

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

1 Scopus citations

Abstract

Object-based storage model is recently widely adopted both in industry and academia to support growingly data intensive applications in high-performance computing. However, the I/O prediction strategies which have been proven effective in traditional parallel file systems, have not been thoroughly studied under this new object-based storage model. There are new challenges introduced from object storage that make traditional prediction systems not work properly. In this paper, we propose a new I/O access prediction system based on provenance analysis on both applications and objects. We argue that the provenance, which contains metadata that describes the history of data, reveals the detailed information about applications and data sets, which can be used to capture the system status and provide accurate I/O prediction efficiently. Our current evaluations based on real-world trace data (Darshan datasets) simulation also confirm that provenance-based prediction system is able to provide accurate predictions for object storage systems.

Original languageEnglish
Title of host publicationProceedings - 14th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing, CCGrid 2014
PublisherIEEE Computer Society
Pages550-551
Number of pages2
ISBN (Print)9781479927838
DOIs
StatePublished - 2014
Event14th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGrid 2014 - Chicago, IL, United States
Duration: May 26 2014May 29 2014

Publication series

NameProceedings - 14th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing, CCGrid 2014

Conference

Conference14th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGrid 2014
CountryUnited States
CityChicago, IL
Period05/26/1405/29/14

Keywords

  • I/O Prediction
  • Object Storage
  • Provenance

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    Dai, D., Chen, Y., Kimpe, D., & Ross, R. (2014). Provenance-based prediction scheme for object storage system in HPC. In Proceedings - 14th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing, CCGrid 2014 (pp. 550-551). [6846497] (Proceedings - 14th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing, CCGrid 2014). IEEE Computer Society. https://doi.org/10.1109/CCGrid.2014.27