Wireless Sensor Networks Distributed Consensus Estimation
This SpringerBrief evaluates the cooperative effort of sensor nodes to accomplish high-level tasks with sensing, data processing and communication. The metrics of network-wide convergence, unbiasedness, consistency and optimality are discussed through net
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Series Editors Stan Zdonik Shashi Shekhar Jonathan Katz Xindong Wu Lakhmi C. Jain David Padua Xuemin (Sherman) Shen Borko Furht V. S. Subrahmanian Martial Hebert Katsushi Ikeuchi Bruno Siciliano Sushil Jajodia Newton Lee
For further volumes: http://www.springer.com/series/10028
Cailian Chen • Shanying Zhu • Xinping Guan Xuemin (Sherman) Shen
Wireless Sensor Networks Distributed Consensus Estimation
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Cailian Chen Department of Automation Shanghai Jiao Tong University Shanghai China
Xinping Guan Department of Automation Shanghai Jiao Tong University Shanghai China
Shanying Zhu Department of Automation Shanghai Jiao Tong University Shanghai China
Xuemin (Sherman) Shen Department of Electrical and Computer Engineering University of Waterloo Waterloo, Ontario Canada
ISSN 2191-5768 ISSN 2191-5776 (electronic) SpringerBriefs in Computer Science ISBN 978-3-319-12378-3 ISBN 978-3-319-12379-0 (eBook) DOI 10.1007/978-3-319-12379-0 Library of Congress Control Number: 2014953216 Springer Cham Heidelberg New York Dordrecht London © The Author(s) 2014 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com)
Preface
The increasing applications of wireless sensor networks (WSNs) witness the fact that the cooperative effort of sensor nodes can accomplish high-level tasks with sensing, data processing, and communication. Instead of sending the raw data to the fusion centers, sensor nodes execute distributed estimation for practical applications by locally carrying out simple computation and transmitting only the required and/or partially processed data. However, the network-wide information fusion capability and efficiency of the distributed estimation remain largely under-investigated. Moreover, the large-scale of WSNs imposes distinguished challenges on systematic analysis and scalable algorithm design to satisfy fundamental estimation criteria. In this monograph, we focus on network-wi
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