NASA Scientific and Technical Aerospace Reports
NASA Scientific and Technical Aerospace Reports
NASA Scientific and Technical Aerospace Reports
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20040121049 Singapore Univ., Singapore<br />
A Design of Metadata Server Cluster in Large Distributed Object-Based Storage<br />
Yan, Jie; Zhu, Yao-Long; Xiong, Hui; Kanagavelu, Renuga; Zhou, Feng; Weon, So-Lih; <strong>NASA</strong>/IEEE MSST 2004 Twelfth<br />
<strong>NASA</strong> Goddard Conference on Mass Storage Systems <strong>and</strong> Technologies in cooperation with the Twenty-First IEEE<br />
Conference on Mass Storage Systems <strong>and</strong> Technologies; April 2004, pp. 199-205; In English; See also 20040121020; No<br />
Copyright; Avail: CASI; A02, Hardcopy<br />
In large distributed Object-based Storage Systems, the performance, availability <strong>and</strong> scalability of the Metadata Server<br />
(MDS) cluster are critical. Traditional MDS cluster suffers from frequent metadata access <strong>and</strong> metadata movement within the<br />
cluster. In this paper, we present a new method called Hashing Partition (HAP) for MDS cluster design to avoid these<br />
overheads. We also demonstrate a design using HAP to achieve good performance of MDS cluster load balancing, failover<br />
<strong>and</strong> scalability.<br />
Author<br />
Metadata; Client Server Systems; Data Storage; Object-Oriented Programming; Distributed Processing; Computer Systems<br />
Design<br />
20040121053 California Univ., Santa Cruz, CA, USA<br />
File System Workload Analysis for Large <strong>Scientific</strong> Computing Applications<br />
Wang, Feng; Xin, Qin; Hong, Bo; Br<strong>and</strong>t, Scott A.; Miller, Ethan L.; Long, Darrell D. E.; McLarty, Tyce T.; <strong>NASA</strong>/IEEE<br />
MSST 2004 Twelfth <strong>NASA</strong> Goddard Conference on Mass Storage Systems <strong>and</strong> Technologies in cooperation with the<br />
Twenty-First IEEE Conference on Mass Storage Systems <strong>and</strong> Technologies; April 2004, pp. 139-152; In English; See also<br />
20040121020<br />
Contract(s)/Grant(s): B520714; W-7405-eng-48; NSF CCR-02-73509<br />
Report No.(s): LLNL-UCRL-CONF-201895; No Copyright; Avail: CASI; A03, Hardcopy<br />
Parallel scientific applications require high-performance I/O support from underlying file systems. A comprehensive<br />
underst<strong>and</strong>ing of the expected workload is therefore essential for the design of high-performance parallel file systems. We<br />
re-examine the workload characteristics in parallel computing environments in the light of recent technology advances <strong>and</strong><br />
new applications. We analyze application traces from a cluster with hundreds of nodes. On average, each application has only<br />
one or two typical request sizes. Large requests from several hundred kilobytes to several megabytes are very common.<br />
Although in some applications small requests account for more than 90% of all requests, almost all of the I/O data are<br />
transferred by large requests. All of these applications show bursty access patterns. More than 65% of write requests have<br />
inter-arrival times within one millisecond in most applications. By running the same benchmark on different file models, we<br />
also find that the write throughput of using an individual output file for each node exceeds that of using a shared file for all<br />
nodes by a factor of 5. This indicates that current file systems are not well optimized for file sharing.<br />
Author<br />
Parallel Processing (Computers); Technology Utilization; Support Systems; Systems Analysis<br />
20040121054 State Univ. of New York, Stony Brook, NY, USA<br />
Reducing Storage Management Costs via Informed User-Based Policies<br />
Zadok, Erez; Osborn, Jeffrey; Shater, Ariye; Wright, Charles; Muniswamy-Reddy, Kiran-Kumar; Nieh, Jason; <strong>NASA</strong>/IEEE<br />
MSST 2004 Twelfth <strong>NASA</strong> Goddard Conference on Mass Storage Systems <strong>and</strong> Technologies in cooperation with the<br />
Twenty-First IEEE Conference on Mass Storage Systems <strong>and</strong> Technologies; April 2004, pp. 193-197; In English; See also<br />
20040121020; No Copyright; Avail: CASI; A01, Hardcopy<br />
Storage management costs continue to increase despite the decrease in hardware costs. We propose a system to reduce<br />
storage maintenance costs by reducing the amount of data backed up <strong>and</strong> reclaiming disk space using various methods (e.g.,<br />
transparently compress old files). Our system also provides a rich set of policies. This allows administrators <strong>and</strong> users to select<br />
the appropriate methods for reclaiming space. Our performance evaluation shows that the overheads under normal use are<br />
negligible. We report space savings on modern systems ranging from 25% to 76%, which result in extending storage lifetimes<br />
by 72%.<br />
Author<br />
Cost Reduction; Policies; Data Management; Data Reduction<br />
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