By Topic

Runtime data declustering over SAN-connected PC cluster system

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Oguchi, M. ; Res. & Dev. Initiative, Chuo Univ., Tokyo, Japan ; Kitsuregawa, M.

Personal computer/workstation (PC/WS) clusters have come to be studied intensively in the field of parallel and distributed computing. From the viewpoint of applications, data intensive applications including data mining and ad-hoc query processing in databases are considered very important for massively parallel processors, in addition to the conventional scientific calculation. Thus, investigating the feasibility of such applications on a PC cluster is meaningful. A PC cluster connected with a storage area network (SAN) is built and evaluated with a data mining application. In the case of a SAN-connected cluster, each node can access all shared disks directly without using a LAN; thus, SAN-connected clusters achieve much better performance than LAN-connected clusters for disk-to-disk copy operations. However, if a lot of nodes access the same shared disk simultaneously, application performance degrades due to the I/O-bottleneck. A runtime data declustering method, in which data is declustered to several other disks dynamically during the execution of the application, is proposed to resolve this problem

Published in:

Data Engineering, 2002. Proceedings. 18th International Conference on

Date of Conference: