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

Degree-guided map-reduce task assignment with data locality constraint

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)
Qiaomin Xie ; Dept. of Electr. & Comput. Eng., Univ. of Illinois at Urbana-Champaign, Urbana, IL, USA ; Yi Lu

The map-reduce framework is used in many data-intensive parallel processing systems. Data locality is an important problem with map-reduce as tasks with local data complete faster than those with remote data. We propose a degree-guided task assignment algorithm, which uses very little extra information than the currently implemented Random Server algorithm. We analyze a simple version of the degree-guided algorithm, called Peeling algorithm, and the Random Server algorithm in a discrete-time model using evolution of random graphs. We characterize the thresholds below which no queueing takes place and compute the effective service rates for both algorithms. The degree-guided algorithm achieves the optimal performance in the region of practical interest and significantly outperforms the Random Server algorithm. The performance characteristics derived from discrete time model are confirmed with simulation in continuous time.

Published in:

Information Theory Proceedings (ISIT), 2012 IEEE International Symposium on

Date of Conference:

1-6 July 2012

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.