By Topic

Distributed learning in mobile sensor networks using cross validation

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
$33 $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)
Songhwai Oh ; School of Electrical Engineering and Computer Science and ASRI, Seoul National University, 151-744, Korea ; Jongeun Choi

Mobile sensor networks can increase sensing coverage both in space and time and robustness against dynamic changes in the environment, compared to stationary wireless sensor networks. For operations in a dynamic or unknown environment, mobile sensors need the capability of learning a suitable model during its operations. However, due to the limited communication bandwidth, it is prohibited to share all measurements with other mobile sensors. In this paper, we propose an efficient distributed learning algorithm based on cross validation for mobile sensor networks, which takes the advantage of a multi-agent system and minimizes the communication overhead while achieving excellent performance, and demonstrate its performance in simulation.

Published in:

49th IEEE Conference on Decision and Control (CDC)

Date of Conference:

15-17 Dec. 2010