Asynchronous object storage with QoS for scientific and commercial big data

Michael J. Brim, David A. Dillow, Sarp Oral, Bradley W. Settlemyer, Feiyi Wang

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

13 Scopus citations

Abstract

This paper presents our design for an asynchronous object storage system intended for use in scientific and commercial big data workloads. Use cases from the target workload domains are used to motivate the key abstractions used in the application programming interface (API). The architecture of the Scalable Object Store (SOS), a prototype object storage system that supports the API's facilities, is presented. The SOS serves as a vehicle for future research into scalable and resilient big data object storage. We briefly review our research into providing efficient storage servers capable of providing quality of service (QoS) contracts relevant for big data use cases.

Original languageEnglish
Title of host publicationProceedings of the 8th Parallel Data Storage Workshop, PDSW 2013 - Held in Conjunction with SC 2013
Subtitle of host publicationThe International Conference for High Performance Computing, Networking, Storage and Analysis
PublisherAssociation for Computing Machinery
Pages7-13
Number of pages7
ISBN (Print)9781450325059
DOIs
StatePublished - 2013
Event8th Parallel Data Storage Workshop, PDSW 2013 - Held in Conjunction with the International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2013 - Denver, CO, United States
Duration: Nov 17 2013Nov 22 2013

Publication series

NameProceedings of the 8th Parallel Data Storage Workshop, PDSW 2013 - Held in Conjunction with SC 2013: The International Conference for High Performance Computing, Networking, Storage and Analysis

Conference

Conference8th Parallel Data Storage Workshop, PDSW 2013 - Held in Conjunction with the International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2013
Country/TerritoryUnited States
CityDenver, CO
Period11/17/1311/22/13

Keywords

  • HPC storage
  • cloud storage
  • object storage
  • storage QoS

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