
Energy-Efficient Area Coverage for Intruder Detection in Sensor Networks
Springer (Publisher)
Published on 7. March 2014
Book
Paperback/Softback
VIII, 97 pages
978-3-319-04647-1 (ISBN)
Description
This Springer Brief presents recent research results on area coverage for intruder detection from an energy-efficient perspective. These results cover a variety of topics, including environmental surveillance and security monitoring. The authors also provide the background and range of applications for area coverage and elaborate on system models such as the formal definition of area coverage and sensing models. Several chapters focus on energy-efficient intruder detection and intruder trapping under the well-known binary sensing model, along with intruder trapping under the probabilistic sensing model. The brief illustrates efficient algorithms rotate the duty of each sensor to prolong the network lifetime and ensure intruder trapping performance. The brief concludes with future directions of the field. Designed for researchers and professionals working with wireless sensor networks, the brief also provides a wide range of applications which are also valuable for advanced-level students interested in efficiency and networking.
More details
Series
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Research
Illustrations
32 s/w Abbildungen
VIII, 97 p. 32 illus.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 6 mm
Weight
197 gr
ISBN-13
978-3-319-04647-1 (9783319046471)
DOI
10.1007/978-3-319-04648-8
Schweitzer Classification
Other editions
Additional editions

Shibo He | Jiming Chen | Junkun Li
Energy-Efficient Area Coverage for Intruder Detection in Sensor Networks
E-Book
02/2014
1st Edition
Springer
€52.99
Available for download
Persons
Zhiguo Shi received the B.S. and Ph.D. degrees in electronic engineering from Zhejiang University, Hangzhou, China, in 2001 and 2006, respectively. Since 2006, he has been a faculty member with the College of Information Science and Electronic Engineering, Zhejiang University, where he is currently a full professor. From 2011 to 2013, he was visiting the Broadband Communications Research Group, University of Waterloo, Waterloo, ON, Canada. His current research interests include array signal processing, target tracking and positioning, IoT system design, and anti-drone system technic and system. He has more than 100 issued patents. He is serving/served as an AE of IEEE Signal Processing Letters, IEEE Transactions on Vehicular Technology, IEEE Network, IET Communications, and Journal of The Franklin Institute. He served as the general co-chair of IEEE SAM 2020, and will serve as the TPC co-chair of IEEE/CIC ICCC 2024
Chaojie Gu received the B.Eng.degree from Harbin Institute of Technology, China, in 2016, and the Ph.D. degree in computer science and engineering from Nanyang Technological University, Singapore, in 2020. He was a Research Fellow with Singtel Cognitive and Artificial Intelligence Lab for Enterprise (SCALE) in 2021. He is an Assistant Professor with the College of Control Science and Engineering, Zhejiang University, Hangzhou, China. His research interests include IoT, industrial IoT, edge computing, and low power wide area network.
Shibo He received the Ph.D. degree in control science and engineering from Zhejiang University, Hangzhou, China, in 2012. He is currently a Professor with Zhejiang University. He was an Associate Research Scientist in 2014 for two months and a Post-Doctoral Scholar from 2012 to 2014 with Arizona State University, Tempe, AZ, USA. From 2010 to 2011, he was a Visiting Scholar with the University of Waterloo, Waterloo, ON, Canada. His current researchinterests include wireless sensor networks, crowdsensing, and big data analysis. Dr. He serves on the Editorial Board of the IEEE Transactions on Vehicular Technology, Springer's Peer-to-Peer Networking and Application and KSII Transactions on Internet and Information Systems. He has been a Guest Editor of Elsevier's Computer Communications and Hinda WI's International Journal of Distributed Sensor Networks.
Kang Hu received the B.Sc. degree from the School of Mechanical Engineering and Electronic Information, China University of Geosciences, Wuhan, China, in 2017, and the Ph.D. degree from Zhejiang University, Hangzhou, China, in 2022. He is currently working for the IoT department of Alibaba. His research interests include low-power wide-area networks and localization.
Content
Introduction to Area Coverage in Sensor Networks.- Energy-Efficient Capture of Stochastic Events in Sensor Networks.- Energy-Efficient Trap Coverage in Sensor Networks.- Trapping Mobile Targets in Sensor Networks.- Conclusion.