Skip to main content
SpringerLink
Log in
Book cover

Information Processing in Sensor Networks

IPSN 2003: Information Processing in Sensor Networks pp 223–238Cite as

A Distributed Algorithm for Managing Multi-target Identities in Wireless Ad-hoc Sensor Networks

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2634))

Abstract

This paper presents a scalable distributed algorithm for computing and maintaining multi-target identity information. The algorithm builds on a novel representational framework, Identity-Mass Flow, to overcome the problem of exponential computational complexity in managing multi-target identity explicitly. The algorithm uses local information to efficiently update the global multi-target identity information represented as a doubly stochastic matrix, and can be efficiently mapped to nodes in a wireless ad hoc sensor network. The paper describes a distributed implementation of the algorithm in sensor networks. Simulation results have validated the Identity-Mass Flow framework and demonstrated the feasibility of the algorithm.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. I. Csiszar, “A geometric interpretation of Darroch and Ratcliff’s generalized iterative scaling”, Annals of Probability, 3, 146–158, 1975.

    Article  MATH  MathSciNet  Google Scholar 

  2. Reid, D.B., “An Algorithm for Tracking Multiple Targets”, IEEE Trans. on Automatic Control, No. 6, December 1979, pp. 843–854

    Google Scholar 

  3. R. R. Tenny and N. R. Sandell Jr., “Detection with Distributed Sensors”, IEEE Transactions on Aerospace and Electronic Systems, Vol. AES-17, No. 4, July 1981

    Google Scholar 

  4. Y. Bar-Shalom and T. E. Fortmann, Tracking and Data Association, Academic Press, New York, 1988

    MATH  Google Scholar 

  5. H. R. Hashemi and I. B. Rhodes, “Decentralized Sequential Detection”, IEEE Transactions on Information Theory, Vol. 35, No. 3, May 1989

    Google Scholar 

  6. T. M. Cover and J. A. Thomas, “Elements of Information Theory”, Wiley, 1991

    Google Scholar 

  7. I. J. Cox and S. L. Hingorani, “An Efficient Implementation of Reid’s Multiple Hypohtesis Tracking Algorithm and its Evaluation for the Purpose of Visual Tracking,” IEEE Trans. on PAMI, Vol 18., No. 2, pp. 138–150, Feb. 1996

    Google Scholar 

  8. P. L. Combettes, “Hilbertian Convex Feasibility Problem: Convergence of Projection Methods” Appl. Math. Optim. 35:311–330, 1997

    MATH  MathSciNet  Google Scholar 

  9. M. Isard and A. Blake, “CONDENSATION — Conditional Density Propagation for Visual Tracking”, Int. J. Computer Vision, 1998

    Google Scholar 

  10. L. J. Guibas, “Kinetic data structures — a state of the art report,” Proc. Workshop Algorithmic Found. Robot., pages 191–209, A. K. Peters, Wellesley, MA, 1998

    Google Scholar 

  11. H. Tao, H.S. Sawhney and R. Kumar, “A Sampling Algorithm for Tracking Multiple Objects,” Proc. of the IEEE Wkshp. on Vision Algorithms, Corfu, Greece, Sep. 1999

    Google Scholar 

  12. H. Pasula, S. Russel, M. Ostland and Y. Ritov, “Tracking Many Objects with many sensors,” Int. Joint Conf. on Artificial Intelligence (IJCAI), Stockholm, pages 1160–1171, 1999.

    Google Scholar 

  13. D. Estrin, R. Govindan, J. Heidemann, and S. Kumar, “Next century challenges: Scalable coordination in sensor networks”, Proceedings of the Fifth Annual International Conference on Mobile Computing and Networks, Seattle, Washington, August 1999

    Google Scholar 

  14. P. Gupta and P.R. Kumar, “The Capacity of Wireless Networks”, IEEE Trans. Inform. Theory, 46(2):388–404, 2000.

    Article  MATH  MathSciNet  Google Scholar 

  15. J. MacCormick and A. Blake, “Probabilistic exclusion and partitioned sampling for multiple object tracking.”, Intl J. Computer Vision, 39(1):57–71, 2000.

    Article  MATH  Google Scholar 

  16. M. Chu, H. Haussecker, and F. Zhao, “Scalable Information-Driven Sensor Query and Routing for ad hoc Heterogeneous Sensor Network”, International Journal of High Performance Computing Applications, 2002

    Google Scholar 

  17. F. Zhao, J. Shin, and J. Reich, “Information Driven Dynamic Sensor Collaboration for Tracking Application”, IEEE Signal Processing Magazine 2002 March

    Google Scholar 

  18. Wei Ye, John Heidemann and Deborah Estrin, “An Energy-Efficient MAC Protocol for Wireless Sensor Networks”, IEEE INFOCOM 2002, June, 2002.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Computer Science Department, Stanford University, Stanford, CA, 94305, USA

    Jaewon Shin & Leonidas J. Guibas

  2. Palo Alto Research Center(PARC), 3333 Coyote Hill Road, Palo Alto, CA, 94304, USA

    Feng Zhao

Authors
  1. Jaewon Shin
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Leonidas J. Guibas
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Feng Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Palo Alto Research Center (PARC), 3333 Coyote Hill Road, Palo Alto, CA, 94304, USA

    Feng Zhao

  2. Computer Science Department, Stanford University, Gates Building 374, Stanford, CA, 94305, USA

    Leonidas Guibas

Rights and permissions

Reprints and permissions

Copyright information

© 2003 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Shin, J., Guibas, L.J., Zhao, F. (2003). A Distributed Algorithm for Managing Multi-target Identities in Wireless Ad-hoc Sensor Networks. In: Zhao, F., Guibas, L. (eds) Information Processing in Sensor Networks. IPSN 2003. Lecture Notes in Computer Science, vol 2634. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36978-3_15

Download citation

  • DOI: https://doi.org/10.1007/3-540-36978-3_15

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-02111-7

  • Online ISBN: 978-3-540-36978-3

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation