Scheduled System Maintenance:
On Monday, April 27th, IEEE Xplore will undergo scheduled maintenance from 1:00 PM - 3:00 PM ET (17:00 - 19:00 UTC). No interruption in service is anticipated.
By Topic

Modeling and Taming Parallel TCP on the Wide Area Network

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)
Lu, D. ; Dept. of Comput. Sci., Northwestern Univ., Evanston, IL, USA ; Qiao, Y. ; Dinda, P.A. ; Bustamante, F.E.

Parallel TCP flows are broadly used in the high performance distributed computing community to enhance network throughput, particularly for large data transfers. Previous research has studied the mechanism by which parallel TCP improves aggregate throughput, but there doesn't exist any practical mechanism to predict its throughput and its impact on the background traffic. In this work, we address how to predict parallel TCP throughput as a function of the number of flows, as well as how to predict the corresponding impact on cross traffic. To the best of our knowledge, we are the first to answer the following question on behalf of a user: what number of parallel flows will give the highest throughput with less than a p% impact on cross traffic? We term this the maximum nondisruptive throughput.We begin by studying the behavior of parallel TCP in simulation to help derive a model for predicting parallel TCP throughput and its impact on cross traffic. Combining this model with some previous findings we derive a simple, yet effective, online advisor. We evaluate our advisor through extensive simulations and wide-area experimentation.

Published in:

Parallel and Distributed Processing Symposium, 2005. Proceedings. 19th IEEE International

Date of Conference:

04-08 April 2005