By Topic

Adaptive dynamic programming for sensor scheduling in energy-constrained wireless sensor 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
$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)
Wendong Xiao ; School of Automation and Electrical Engineering, University of Science & Technology Beijing, 30 XueYuan Road, Haidian District, Beijing, China ; Ruizhuo Song

In this paper, we propose an adaptive sensor scheduling scheme to maximize the network lifetime for energy-constrained wireless sensor networks (WSNs) using adaptive dynamic programming (ADP) method. Based on Kalman filter (KF) prediction, the problem is firstly formulated as an infinite-step constrained maximum optimal control problem with the estimation accuracy constraint at each step. Then, a novel adaptive scheduling scheme based on iterative ADP algorithm is proposed as the solution where the predicted performance index is approximated by a neural network. Analysis of the proposed solution is given which shows that the performance index converges to the optimum. A simulation example is employed to illustrate the applicability of the proposed method.

Published in:

Information Fusion (FUSION), 2012 15th International Conference on

Date of Conference:

9-12 July 2012