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Asynchronous Object Storage with QoS for Scientific and Commercial Big Data...

by Michael J Brim, David A Dillow, Hakki S Oral, Bradley W Settlemyer, Feiyi Wang
Publication Type
Conference Paper
Publication Date
Conference Name
8th Parallel Data Storage Workshop
Conference Location
Denver, Colorado, United States of America
Conference Sponsor
Conference Date

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 do- mains 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 stor- age 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.