Cart (Loading....) | Create Account
Close category search window
 

Multi-Replication with Intelligent Staging in Data-Intensive Grid Applications

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

4 Author(s)
Machida, Y. ; Tokyo Inst. of Technol. ; Takizawa, S. ; Nakada, H. ; Matsuoka, S.

Existing data grid scheduling systems handle huge data I/O via replica location services coupled with simple staging, decoupled from scheduling of computing tasks. However, when the application/workflow scales, we observe considerable degradations in performance, compared to processing within a tightly-coupled cluster. For example, when numerous nodes access the same set of files simultaneously, major performance degradation occurs even if replicas are used, due to bottlenecks that manifest in the infrastructure. Instead of resorting to expensive solutions such as parallel file systems, we propose alleviating the situation by tightly coupling replica and data transfer management with computation scheduling. In particular we propose three techniques: (1) dynamic aggregation and O(1) replication of data-staging requests across multiple nodes using a multi-replication framework, (2) replica-centric scheduling - data re-use and time-to-replication as compute scheduling metrics on the grid and (3) overlapped execution of data staging and compute bound tasks. Early benchmark results implemented in our prototype Condor-like grid scheduling system demonstrate that the techniques are quite effective in eliminating much of the overhead in data transfers in many cases

Published in:

Grid Computing, 7th IEEE/ACM International Conference on

Date of Conference:

28-29 Sept. 2006

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.