By Topic

Sequential Monte Carlo inference of internal delays in nonstationary data networks

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)
Coates, M.J. ; Dept. of Electr. & Comput. Eng., Rice Univ., Houston, TX, USA ; Nowak, R.D.

On-line, spatially localized information about internal network performance can greatly assist dynamic routing algorithms and traffic transmission protocols. However, it is impractical to measure network traffic at all points in the network. A promising alternative is to measure only at the edge of the network and infer internal behavior from these measurements. We concentrate on the estimation and localization of internal delays based on end-to-end delay measurements from a source to receivers. We propose a sequential Monte Carlo (SMC) procedure capable of tracking nonstationary network behavior and estimating time-varying, internal delay characteristics. Simulation experiments demonstrate the performance of the SMC approach

Published in:

Signal Processing, IEEE Transactions on  (Volume:50 ,  Issue: 2 )