Skip to main content

Network Synchronization and Localization Based on Stolen Signals

  • Conference paper
Structural Information and Communication Complexity (SIROCCO 2011)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6796))

Abstract

We consider an anchor-free, relative localization and synchronization problem where a set of n receiver nodes and m wireless signal sources are independently, uniformly, and randomly distributed in a disk in the plane. The signals can be distinguished and their capture times can be measured. At the beginning neither the positions of the signal sources and receivers are known nor the sending moments of the signals. Now each receiver captures each signal after its constant speed journey over the unknown distance between signal source and receiver position. Given these n m capture times the task is to compute the relative distances between all synchronized receivers. In a more generalized setting the receiver nodes have no synchronized clocks and need to be synchronized from the capture times of the stolen signals.

For unsynchronized receivers we can compute in time \({\ensuremath \cal O}(n m)\) an approximation of the positions and the clock offset within an absolute error of \({\ensuremath \cal O}\left(\sqrt{\frac{\log m}{m}}\right)\) with probability 1 − m − c − e − cn (for any \(c\in {\ensuremath \cal O}(1)\) and some c′ > 0).

For synchronized receivers we can compute in time O(n m) an approximation of the correct relative positions within an absolute error margin of \( {\cal O}\left(\frac{\log^2 m}{m^2}\right)\) with probability 1 − m − c − e − cn. This error bound holds also for unsynchronized receivers if we consider a normal distribution of the sound signals, or if the sound signals are randomly distributed in a surrounding larger disk.

If the receiver nodes are connected via an ad hoc network we present a distributed algorithm which needs at most O(n m logn) messages in total to compute the approximate positions and clock offsets for the network within an absolute error of \({\ensuremath \cal O}\left(\sqrt{\frac{\log m}{m}}\right)\) with probability 1 − n − c if m > n.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
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

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Schindelhauer, C., Lotker, Z., Wendeberg, J.: Brief Announcement: Network Synchronization and Localization Based on Stolen Signals. In: Proceedings of the 30th Annual ACM Symposium on Principles of Distributed Computing, PODC (2011)

    Google Scholar 

  2. Sichitiu, M.L., Ramadurai, V.: Localization of Wireless Sensor Networks with a Mobile Beacon. In: Proceedings of the First IEEE Conference on Mobile Ad-hoc and Sensor Systems, pp. 174–183 (2004)

    Google Scholar 

  3. Ferris, B., Hähnel, D., Fox, D.: Gaussian Processes for Signal Strength-Based Location Estimation. In: Proceedings of Robotics: Science and Systems Conference, RSS (2006)

    Google Scholar 

  4. Priyantha, N.B., Chakraborty, A., Balakrishnan, H.: The Cricket Location-Support System. In: MobiCom 2000: Proceedings of the 6th annual international conference on Mobile computing and networking, pp. 32–43 (2000)

    Google Scholar 

  5. Savvides, A., Han, C.C., Strivastava, M.B.: Dynamic Fine-Grained Localization in Ad-Hoc Networks of Sensors. In: Proceedings of the 7th annual international conference on Mobile Computing and Networking, pp. 166–179. ACM, New York (2001)

    Google Scholar 

  6. Khan, U.A., Kar, S., Moura, J.M.F.: Distributed Sensor Localization in Random Environments using Minimal Number of Anchor Nodes. IEEE Transactions on Signal Processing 57(5), 2000–2016 (2009)

    Article  MathSciNet  Google Scholar 

  7. Biswas, P., Ye, Y.: Semidefinite Programming for Ad Hoc Wireless Sensor Network Localization. In: IPSN 2004: Proceedings of the 3rd international symposium on Information processing in sensor networks, pp. 46–54. ACM, New York (2004)

    Google Scholar 

  8. Savarese, C., Rabaey, J., Langendoen, K.: Robust Positioning Algorithms for Distributed Ad-Hoc Wireless Sensor Networks. In: USENIX Technical Annual Conference, Monterey, CA, vol. 2 (2002)

    Google Scholar 

  9. Savvides, A., Park, H., Srivastava, M.B.: The Bits and Flops of the N-hop Multilateration Primitive For Node Localization Problems. In: Proceedings of the 1st ACM International Workshop on Wireless Sensor Networks and Applications, p. 121. ACM, New York (2002)

    Google Scholar 

  10. Torrieri, D.J.: Statistical Theory of Passive Location Systems. IEEE Transactions on Aerospace and Electronic Systems AES-20(2), 183–198 (1984)

    Article  Google Scholar 

  11. Gillette, M.D., Silverman, H.F.: A Linear Closed-Form Algorithm for Source Localization From Time-Differences of Arrival. IEEE Signal Processing Letters 15, 1–4 (2008)

    Article  Google Scholar 

  12. Biswas, R., Thrun, S.: A Passive Approach to Sensor Network Localization. In: Proceedings of the 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2004), vol. 2, pp. 1544–1549 (2004)

    Google Scholar 

  13. Biswas, R., Thrun, S.: A Distributed Approach to Passive Localization for Sensor Networks. In: Proceedings of the National Conference on Artificial Intelligence, vol. 20, p. 1248. AAAI Press, MIT Press (1999)

    Google Scholar 

  14. Pollefeys, M., Nister, D.: Direct computation of sound and microphone locations from time-difference-of-arrival data. In: IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 2445–2448. IEEE, Los Alamitos (2008)

    Google Scholar 

  15. Doherty, L., El Ghaoui, L.: Convex Position Estimation in Wireless Sensor Networks. In: INFOCOM 2001. Proceedings of the Twentieth Annual Joint Conference of the IEEE Computer and Communications Societies, vol. 3, pp. 1655–1663. IEEE, Los Alamitos (2002)

    Google Scholar 

  16. Simic, S.N., Sastry, S.: Distributed Localization in Wireless Ad Hoc Networks. UC Berkeley ERL report (2001)

    Google Scholar 

  17. Lotker, Z., de Albeniz, M.M., Pérénnes, S.: Range-Free Ranking in Sensors Networks and Its Applications to Localization. In: Nikolaidis, I., Barbeau, M., An, H.-C. (eds.) ADHOC-NOW 2004. LNCS, vol. 3158, pp. 158–171. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  18. Kröller, A., Fekete, S., Pfisterer, D., Fischer, S.: Deterministic boundary recognition and topology extraction for large sensor networks. In: Proceedings of the seventeenth annual ACM-SIAM Symposium on Discrete Algorithms, pp. 1000–1009. ACM, New York (2006)

    Google Scholar 

  19. Janson, T., Schindelhauer, C., Wendeberg, J.: Self-Localization Application for iPhone using only Ambient Sound Signals. In: Proceedings of the 2010 International Conference on Indoor Positioning and Indoor Navigation (IPIN), pp. 259–268 (November 2010)

    Google Scholar 

  20. Anta, A.F., Mosteiro, M.A., Thraves, C.: Deterministic Recurrent Communication and Synchronization in Restricted Sensor Networks. INRIA RR 486277 (2010)

    Google Scholar 

  21. Sundararaman, B., Buy, U., Kshemkalyani, A.D.: Clock Synchronization for Wireless Sensor Networks: A Survey. Ad Hoc Networks 3(3), 281–323 (2005)

    Article  Google Scholar 

  22. Langendoen, K., Reijers, N.: Distributed localization in wireless sensor networks: a quantitative comparison. Computer Networks 43(4), 499–518 (2003)

    Article  MATH  Google Scholar 

  23. Stupp, G., Sidi, M.: The expected uncertainty of range-free localization protocols in sensor networks. Theoretical Computer Science 344(1), 86–99 (2005)

    Article  MATH  MathSciNet  Google Scholar 

  24. Savvides, A., Garber, W.L., Moses, R.L., Srivastava, M.B.: An Analysis of Error Inducing Parameters in Multihop Sensor Node Localization. IEEE Transactions on Mobile Computing, 567–577 (2005)

    Google Scholar 

  25. Dulman, S., Havinga, P., Baggio, A., Langendoen, K.: Revisiting the Cramer-Rao Bound for Localization Algorithms. In: 4th IEEE/ACM DCOSS Work-in-progress paper (2008)

    Google Scholar 

  26. Moses, R.L., Krishnamurthy, D., Patterson, R.M.: A Self-Localization Method for Wireless Sensor Networks. EURASIP Journal on Advances in Signal Processing, 348–358 (2003)

    Google Scholar 

  27. Stewénius, H.: Gröbner Basis Methods for Minimal Problems in Computer Vision. PhD thesis, Lund University (April 2005)

    Google Scholar 

  28. Eren, T., Goldenberg, D.K., Whiteley, W., Yang, Y.R., Morse, A.S., Anderson, B.D.O., Belhumeur, P.N.: Rigidity, Computation, and Randomization in Network Localization. In: INFOCOM 2004. Twenty-Third Annual Joint Conference of the IEEE Computer and Communications Societies, vol. 4, pp. 2673–2684. IEEE, Los Alamitos (2004)

    Google Scholar 

  29. Efrat, A., Forrester, D., Iyer, A., Kobourov, S.G., Erten, C., Kilic, O.: Force-Directed Approaches to Sensor Localization. ACM Transactions on Sensor Networks (TOSN) 7(3), 1–25 (2010)

    Article  Google Scholar 

  30. Calafiore, G.C., Carlone, L., Wei, M.: A Distributed Gauss-Newton Approach for Range-based Localization of Multi Agent Formations. In: 2010 IEEE International Symposium on Computer-Aided Control System Design (CACSD), pp. 1152–1157. IEEE, Los Alamitos (2010)

    Chapter  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Schindelhauer, C., Lotker, Z., Wendeberg, J. (2011). Network Synchronization and Localization Based on Stolen Signals. In: Kosowski, A., Yamashita, M. (eds) Structural Information and Communication Complexity. SIROCCO 2011. Lecture Notes in Computer Science, vol 6796. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22212-2_26

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-22212-2_26

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-22211-5

  • Online ISBN: 978-3-642-22212-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics