Asynchronous object storage with QoS for scientific and commercial big data

  • Authors:
  • Michael J. Brim;David A. Dillow;Sarp Oral;Bradley W. Settlemyer;Feiyi Wang

  • Affiliations:
  • Oak Ridge National Laboratory, Oak Ridge, TN;Oak Ridge National Laboratory, Oak Ridge, TN;Oak Ridge National Laboratory, Oak Ridge, TN;Oak Ridge National Laboratory, Oak Ridge, TN;Oak Ridge National Laboratory, Oak Ridge, TN

  • Venue:
  • PDSW '13 Proceedings of the 8th Parallel Data Storage Workshop
  • Year:
  • 2013

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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.