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

Exploring spatial correlation for link quality estimation in 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
$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)
Yingqi Xu ; Pennsylvania State Univ., University Park, PA ; Lee, W.-C.

The irregularity in quality of wireless communication links poses significant research challenges in wireless sensor network design. Dynamic network conditions and environmental factors make an online, self-adapted link quality estimation mechanism within sensor nodes a necessity for making routing decisions and improving network performance. In this paper, we present a weighted regression algorithm for efficient and accurate estimation of link quality in wireless sensor networks. This algorithm captures the spatial correlation in quality of links between a sensor node and its neighbor nodes, such that the quality of a link to a neighbor node can be estimated based on the quality of links to other nodes geographically close. We evaluate the proposed algorithm using a trace-based simulator which takes into account the variances of link quality over time and spatial locations. The experimental results show that the weighted regression algorithm is able to achieve more accurate estimates than WMEWMA, a state-of-the-art link quality estimator, at a much lower communication cost

Published in:

Pervasive Computing and Communications, 2006. PerCom 2006. Fourth Annual IEEE International Conference on

Date of Conference:

13-17 March 2006

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.