FlexDAS: A flexible direct attached storage for I/O intensive applications

Takatsugu Ono, Yotaro Konishi, Teruo Tanimoto, Noboru Iwamatsu, Takashi Miyoshi, Jun Tanaka

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

5 被引用数 (Scopus)

抄録

Big data analysis and a data storing applications require a huge volume of storage and a high I/O performance. Applications can achieve high levels of performance and cost efficiency by exploiting the high I/O performances of direct attached storages (DAS) such as internal HDDs. With the size of stored data ever increasing, it will be difficult to replace servers since internal HDDs contain huge amounts of data. In response to this issue, we propose FlexDAS, which improves the flexibility of direct attached storage by using a disk area network (DAN) without degrading the I/O performance. We developed a prototype FlexDAS switch and quantitatively evaluated the architecture. Results show that the FlexDAS switch can disconnect and connect the HDD to the server in just 1.16 seconds. The I/O performances of the disks connected via the FlexDAS switch were almost the same as the conventional DAS architecture.

本文言語英語
ホスト出版物のタイトルProceedings - 2014 IEEE International Conference on Big Data, IEEE Big Data 2014
編集者Wo Chang, Jun Huan, Nick Cercone, Saumyadipta Pyne, Vasant Honavar, Jimmy Lin, Xiaohua Tony Hu, Charu Aggarwal, Bamshad Mobasher, Jian Pei, Raghunath Nambiar
出版社Institute of Electrical and Electronics Engineers Inc.
ページ147-152
ページ数6
ISBN(電子版)9781479956654
DOI
出版ステータス出版済み - 1 7 2015
外部発表はい
イベント2nd IEEE International Conference on Big Data, IEEE Big Data 2014 - Washington, 米国
継続期間: 10 27 201410 30 2014

出版物シリーズ

名前Proceedings - 2014 IEEE International Conference on Big Data, IEEE Big Data 2014

その他

その他2nd IEEE International Conference on Big Data, IEEE Big Data 2014
国/地域米国
CityWashington
Period10/27/1410/30/14

All Science Journal Classification (ASJC) codes

  • 人工知能
  • 情報システム

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