November 2013

Conference Paper

Asynchronous Object Storage with QoS for Scientific and Commercial Big Data

By:
Brim, Michael J; Dillow, David A; Oral, Hakki S; Settlemyer, Bradley W; Wang, Feiyi
Publication Date:
November 2013
Conference Name:
8th Parallel Data Storage Workshop
Conference Location:
Denver, Colorado, United States of America
Conference Sponsor:
ACM SIGHPC

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 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.