Chew analyzer: Workload-aware data management across differentiated storage pools

Xiongzi Ge, Xuchao Xie, David H.C. Du, Pradeep Ganesan, Dennis Hahn

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

Abstract

In multi-Tier storage systems, moving data from one tier to the next can be inefficient. And because each type of storage device has its own idiosyncrasies with respect to the workloads that it can best support, unnecessary data movement might result. In this paper, we explore a fully connected storage architecture in which data can move from any storage pool to another. We propose a Chunk-level storage-Aware workload Analyzer framework, abbreviated as ChewAnalyzer, to facilitate efficient data placement. Access patterns are characterized in a flexible way by a collection of I/O accesses to a data chunk. ChewAnalyzer employs a Hierarchical Classifier [1] to analyze the chunk patterns step by step. In each classification step, the Chunk Placement Recommender suggests new data placement policies according to the device properties. Based on the analysis of access pattern changes, the Storage Manager can adequately distribute or migrate the data chunks across different storage pools. Our experimental results show that ChewAnalyzer improves the initial data placement and that it migrates data into the proper pools directly and efficiently.

Original languageEnglish (US)
Title of host publicationProceedings - 26th IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, MASCOTS 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages94-101
Number of pages8
ISBN (Electronic)9781538668863
DOIs
StatePublished - Nov 7 2018
Event26th IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, MASCOTS 2018 - Milwaukee, United States
Duration: Sep 25 2018Sep 28 2018

Publication series

NameProceedings - 26th IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, MASCOTS 2018

Other

Other26th IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, MASCOTS 2018
CountryUnited States
CityMilwaukee
Period9/25/189/28/18

Bibliographical note

Funding Information:
We would like to thank the anonymous MASCOTS reviewers for their helpful comments to improve the previous draft of this paper. We also thank Al Andux, Ajay Bakre, Jerry Fredin, and Art Harkin from NetApp and all the members in the CRIS group for their suggestions and support. This work was partially supported by NSF awards 1305237, 1812537, 1421913, 1439622 and 1525617.

Keywords

  • Data movement
  • Data placement
  • Fully connected storage
  • Hierarchical Classifier
  • Storage

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