research-article

Analytic evaluation of target detection in heterogeneous wireless sensor networks

Authors:

Radha Poovendran,

James A. RitceyAuthors Info & Claims

ACM Transactions on Sensor Networks (TOSN), Volume 5, Issue 2

Article No.: 18, Pages 1 - 38

https://doi.org/10.1145/1498915.1498924

Published: 03 April 2009 Publication History

Abstract

In this article, we address the problem of target detection in Wireless Sensor Networks (WSNs). We formulate the target detection problem as a line-set intersection problem and use integral geometry to analytically characterize the probability of target detection for both stochastic and deterministic deployments. Compared to previous work, we analyze WSNs where sensors have heterogeneous sensing capabilities. For the stochastic case, we evaluate the probability that the target is detected by at least k sensors and compute the free path until the target is first detected. For the deterministic case, we show an analogy between the target detection problem and the problem of minimizing the average symbol error probability in 2D digital modulation schemes. Motivated by this analogy, we propose a heuristic sensor placement algorithm, called DATE, that makes use of well-known signal constellations for determining good WSN constellations. We also propose a heuristic called CDATE for connected WSN constellations, that yields high target detection probability.

References

[1]

Aslam, J., Butler, Z., Constantin, F., Crespi, V., Cybenko, G., and Rus, D. 2003. Tracking a moving object with a binary sensor network. In Proceedings of the 1st International Conference on Embedded Networked Sensor Systems, 150--161.

Digital Library

[2]

Benedetto, S. and Biglieri, E. 1999. Principles of Digital Transmission: With Wireless Applications. Kluwer Academic.

Digital Library

[3]

Boutros, J., Viterbo, E., Rastello, C., and Belfiore, J. 1996. Good lattice constellations for both Rayleigh fading and Gaussian channels. IEEE Trans. Information Theory 42, 2, 502--518.

Digital Library

[4]

Cao, Q., Yan, T., Stankovic, J., and Abdelzaher, T. 2005. Analysis of target detection performance for wireless sensor networks. DCOSS05. http//www.cs.virginia.edu/~stankovic/psfiles/qingcao1568953971.pdf.

Digital Library

[5]

Cho, E. 2002. Grid coverage for surveillance and target location in distributed sensor networks. IEEE Trans. Comput. 51, 12, 1449.

Digital Library

[6]

Clouqueur, T., Phipatanasuphorn, V., Ramanathan, P., and Saluja, K. 2002. Sensor deployment strategy for target detection. In Proceedings of the 1st ACM International Workshop on Wireless Sensor Networks and Applications, 42--48.

Digital Library

[7]

Clouqueur, T., Saluja, K., and Ramanathan, P. 2004. Fault tolerance in collaborative sensor networks for target detection. IEEE Trans. Comput. 53, 3, 320--333.

Digital Library

[8]

Conway, J. and Sloane, N. 1998. Sphere Packings, Lattices and Groups. Springer.

Digital Library

[9]

Dousse, O., Tavoularis, C., and Thiran, P. 2006. Delay of intrusion detection in wireless sensor networks. In Proceedings of the 7th ACM International Symposium on Mobile Ad Hoc Networking and Mobile Computing, 155--165.

Digital Library

[10]

Feller, W. 1971. An introduction to probability theory and its applications. Wiley Series in Probability and Mathematical Statistics 3rd ed. Wiley, New York.

[11]

Flanders, H. 1989. Differential Forms With Applications to the Physical Sciences. Dover.

[12]

Gui, C. and Mohapatra, P. 2004. Power conservation and quality of surveillance in target tracking sensor networks. In Proceedings of the 10th Annual International Conference on Mobile Computing and Networking, 129--143.

Digital Library

[13]

Itô, K. 1984. Introduction to Probability Theory. Cambridge University Press.

[14]

Koushanfar, F., Slijepcevic, S., Potkonjak, M., and Sangiovanni-Vincentelli, A. 2002. Error-Tolerant multimodal sensor fusion. In IEEE CAS Workshop on Wireless Communication and Networking.

[15]

Kumar, S., Lai, T., and Arora, A. 2005. Barrier coverage with wireless sensors. In Proceedings of the 11th Annual International Conference on Mobile Computing and Networking, 284--298.

Digital Library

[16]

Lazos, L. and Poovendran, R. 2006. Stochastic coverage in heterogeneous sensor networks. ACM Trans. Sensor Netw. 325--358.

Digital Library

[17]

Lazos, L., Poovendran, R., and Ritcey, J. 2007a. On the deployment of heterogeneous sensor networks for detection of mobile targets. In Proceedings of the 5th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt'07).

[18]

Lazos, L., Poovendran, R., and Ritcey, J. 2007b. Probabilistic detection of mobile targets in heterogeneous sensor networks. In Proceedings of the 6th International Conference on Information Processing in Sensor Networks, 519--528.

Digital Library

[19]

Meguerdichian, S., Koushanfar, F., Potkonjak, M., and Srivastava, M. 2001. Coverage problems in wireless ad-hoc sensor networks. In Proceedings of the 20th Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM 01) 3.

[20]

Meguerdichian, S., Koushanfar, F., Qu, G., and Potkonjak, M. 2001. Exposure in wireless ad-hoc sensor networks. In Proceedings of the 7th Annual International Conference on Mobile Computing and Networking, 139--150.

Digital Library

[21]

Reuleaux, F. 1963. The Kinematics of Machinery. Dover, New York.

[22]

Santaló, L. 2004. Integral Geometry and Geometric Probability. Cambridge University Press.

[23]

Solomon, H. 1978. Geometric Probability. Society for Industrial and Applied Mathematics Philadelphia, PA.

[24]

Sylvester, J. 1890. On a funicular solution of Buffon's “problem of the needle” in its most general form. Acta Mathematica 14, 1, 185--205.

[25]

Yang, H. and Sikdar, B. 2003. A protocol for tracking mobile targets using sensor networks. In Proceedings of the 1st IEEE International Workshop on Sensor Network Protocols and Applications, 71--81.

Cited By

Sharma AChauhan S(2020)Sensor Fusion for Distributed Detection of Mobile Intruders in Surveillance Wireless Sensor NetworksIEEE Sensors Journal10.1109/JSEN.2020.300982820:24(15224-15231)Online publication date: 15-Dec-2020
https://doi.org/10.1109/JSEN.2020.3009828
Hoyingcharoen PTeerapabkajorndet W(2019)Expected Probabilistic Detection and Sink Connectivity in Wireless Sensor NetworksIEEE Sensors Journal10.1109/JSEN.2019.290180219:12(4480-4493)Online publication date: 15-Jun-2019
https://doi.org/10.1109/JSEN.2019.2901802
Halder SGhosal AConti M(2019)Efficient Physical Intrusion Detection in Internet of Things: A Node Deployment ApproachComputer Networks10.1016/j.comnet.2019.02.019Online publication date: Mar-2019
https://doi.org/10.1016/j.comnet.2019.02.019
Show More Cited By

Index Terms

Analytic evaluation of target detection in heterogeneous wireless sensor networks
1. Computer systems organization
  1. Architectures
    1. Distributed architectures
2. Networks
  1. Network architectures
  2. Network properties
    1. Network structure

Recommendations

Improving mobile target detection on randomly deployed sensor networks

This paper investigates the detection performance of randomly deployed wireless sensor networks. It addresses the problem of detecting mobile targets that have continuous movement. We categorise these targets into two classes. The first type is rational ...
Prolonging network lifetime under probabilistic target coverage in wireless mobile sensor networks

One of the main operations in wireless sensor networks is the surveillance of a set of events (targets) that occur in the field. In practice, a node monitors an event accurately when it is located closer to it, while the opposite happens when the node ...
The Steady Clustering Scheme for Heterogeneous Wireless Sensor Networks
UIC-ATC '09: Proceedings of the 2009 Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing

To reduce energy consumption is an important topic in WSN (wireless sensor networks). One of the popular protocols for energy-efficient WSN is called LEACH (Low-Energy Adaptive Clustering Hierarchy) which is a clustering algorithm designed for ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Transactions on Sensor Networks

ACM Transactions on Sensor Networks Volume 5, Issue 2

March 2009

284 pages

ISSN:1550-4859

EISSN:1550-4867

DOI:10.1145/1498915

Issue’s Table of Contents

Copyright © 2009 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Journal Family

ACM Journals for the Design of Smart and Connected Systems

Publication History

Published: 03 April 2009

Accepted: 01 June 2008

Revised: 01 May 2008

Received: 01 October 2007

Published in TOSN Volume 5, Issue 2

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article
Research
Refereed

Funding Sources

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

41
Total Citations
View Citations
740
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 16 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

Sharma AChauhan S(2020)Sensor Fusion for Distributed Detection of Mobile Intruders in Surveillance Wireless Sensor NetworksIEEE Sensors Journal10.1109/JSEN.2020.300982820:24(15224-15231)Online publication date: 15-Dec-2020
https://doi.org/10.1109/JSEN.2020.3009828
Hoyingcharoen PTeerapabkajorndet W(2019)Expected Probabilistic Detection and Sink Connectivity in Wireless Sensor NetworksIEEE Sensors Journal10.1109/JSEN.2019.290180219:12(4480-4493)Online publication date: 15-Jun-2019
https://doi.org/10.1109/JSEN.2019.2901802
Halder SGhosal AConti M(2019)Efficient Physical Intrusion Detection in Internet of Things: A Node Deployment ApproachComputer Networks10.1016/j.comnet.2019.02.019Online publication date: Mar-2019
https://doi.org/10.1016/j.comnet.2019.02.019
Hammoudeh MAl-Fayez FLloyd HNewman RAdebisi BBounceur AAbuarqoub A(2017)A Wireless Sensor Network Border Monitoring System: Deployment Issues and Routing ProtocolsIEEE Sensors Journal10.1109/JSEN.2017.267250117:8(2572-2582)Online publication date: 15-Apr-2017
https://doi.org/10.1109/JSEN.2017.2672501
Avci BTrajcevski GTamassia RScheuermann PZhou F(2017)Efficient detection of motion-trend predicates in wireless sensor networksComputer Communications10.1016/j.comcom.2016.08.012101:C(26-43)Online publication date: 15-Mar-2017
https://dl.acm.org/doi/10.1016/j.comcom.2016.08.012
Kaiwartya OKumar SAbdullah A(2017)Analytical Model of Deployment Methods for Application of Sensors in Non-hostile EnvironmentWireless Personal Communications: An International Journal10.1007/s11277-017-4584-697:1(1517-1536)Online publication date: 1-Nov-2017
https://dl.acm.org/doi/10.1007/s11277-017-4584-6
Wang YChu WFields SHeinemann CReiter Z(2016)Detection of Intelligent Intruders in Wireless Sensor NetworksFuture Internet10.3390/fi80100028:4(2)Online publication date: 20-Jan-2016
https://doi.org/10.3390/fi8010002
Liu LFu RHe YZhang Y(2014)Deployment Strategy in Distributed Underwater Sensor NetworksApplied Mechanics and Materials10.4028/www.scientific.net/AMM.602-605.3643602-605(3643-3647)Online publication date: Aug-2014
https://doi.org/10.4028/www.scientific.net/AMM.602-605.3643
Ghosal AHalder S(2014)Tailor-Made Gaussian Distribution for Intrusion Detection in Wireless Sensor NetworksProceedings of the 2014 IEEE 11th Intl Conf on Ubiquitous Intelligence and Computing and 2014 IEEE 11th Intl Conf on Autonomic and Trusted Computing and 2014 IEEE 14th Intl Conf on Scalable Computing and Communications and Its Associated Workshops (UIC-ATC-ScalCom)10.1109/UIC-ATC-ScalCom.2014.133(406-411)Online publication date: 9-Dec-2014
https://dl.acm.org/doi/10.1109/UIC-ATC-ScalCom.2014.133
Cho HChen CShih TChao H(2014)Survey on underwater delay/disruption tolerant wireless sensor network routingIET Wireless Sensor Systems10.1049/iet-wss.2013.01184:3(112-121)Online publication date: Sep-2014
https://doi.org/10.1049/iet-wss.2013.0118
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Article

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Issue’s Table of Contents