Skip to main content
SpringerLink
Log in

Algorithmic Aspects of Sensor Localization

  • Chapter
  • First Online:
Theoretical Aspects of Distributed Computing in Sensor Networks

Abstract

Identifying locations of nodes in wireless sensor networks (WSNs) is critical to both network operations and most application level tasks. Sensor nodes equipped with geographical positioning system (GPS) devices are aware of their locations at a precision level of few meters. However, installing GPS devices on a large number of sensor nodes not only is expensive but also affects the form factor of these nodes. Moreover, GPS-based localization is not applicable in the indoor environments such as buildings. There exists an extensive body of research literature that aims at obtaining absolute locations as well as relative spatial locations of nodes in a WSN without requiring specialized hardware at large scale. The typical approach consists of employing only a limited number of anchor nodes that are aware of their own locations, and then trying to infer locations of non-anchor nodes using graph-theoretic, geometric, statistical, optimization, and machine learning techniques. Thus, the literature represents a very rich ensemble of algorithmic techniques applicable to low power, highly distributed nodes with resource-optimal computations. In this chapter we take a close look at the algorithmic aspects of various important localization techniques for WSNs.

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

Access this chapter

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 EPUB and 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
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover 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

References

  1. S. Capkun, M. Hamdi, and J.-P. Hubaux. GPS-free positioning in mobile ad-hoc networks. Proceedings of the 34th Annual Hawaii International Conference on System Sciences, page 9008, 2001.

    Google Scholar 

  2. G. Mao and B. Fidan. Localization algorithms and strategies for wireless sensor networks. Information Science Reference – Imprint of: IGI Publishing, pages 1–526, 2009.

    Google Scholar 

  3. A. Savvides, M. Srivastava, L. Girod, and D. Estrin. Localization in sensor networks. In C. S. Raghavendra, K. M. Sivalingam, and T. Znati, editors, Wireless Sensor Networks, Kluwer, Norwell, MA, pages 327–349, 2004.

    Chapter  Google Scholar 

  4. J. Bachrach and C. Taylor. Localization in sensor networks. In I. Stojmenovic editor Handbook of Sensor Networks: Algorithms and Architectures, Wiley, New York, NY, ch. 9, pages 277–310, 2005.

    Google Scholar 

  5. G. Mao, B. Fidan, and B. D. O. Anderson. Wireless sensor network localization techniques. Computer Network, 51(10):2529–2553, 2007.

    Article  MATH  Google Scholar 

  6. N. Bulusu, J. Heidemann, and D. Estrin. GPS-less low-cost outdoor localization for very small devices. IEEE Personal Communications Magazine [see also IEEE Wireless Commun. Mag.], 7(5):28–34, 2000.

    Google Scholar 

  7. P. Agrawal, R. K. Ghosh, and S. K. Das. Localization of wireless sensor nodes using proximity information. In ICCCN 2007: The 16th International Conference on Computer Communications and Networks, pages 485–490, 2007.

    Google Scholar 

  8. R. Salomon. Precise localization in coarse-grained localization algorithms through local learning. In IEEE SECON 2005: Second Annual IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks, pages 533–540, 2005.

    Google Scholar 

  9. T. He, C. Huang, B. M. Blum, J. A. Stankovic, and T. F. Abdelzaher. Range-free localization and its impact on large scale sensor networks, Transactions on Embedded Computing Systems, 4(4):877–906, 2005.

    Article  Google Scholar 

  10. H.-C. Chu and R.-H. Jan. A GPS-less, outdoor, self-positioning method for wireless sensor networks. Ad Hoc Networks, 5(5):547–557, 2007.

    Article  Google Scholar 

  11. R. Nagpal, H. Shrobe, and J. Bachrach. Organizing a global coordinate system from local information on an ad hoc sensor network. In IPSN 2003: Proceedings of the 3rd International Symposium on Information Processing in Sensor Networks, 2003.

    Google Scholar 

  12. D. Niculescu and B. Nath. Ad hoc positioning system (APS). IEEE GLOBECOM 2001, pages 2926–2931, 2001.

    Google Scholar 

  13. Y. Shang, W. Ruml, Y. Zhang, and M. P. J. Fromherz. Localization from mere connectivity. In MobiHoc 2003: Proceedings of the 4th ACM International Symposium on Mobile Ad Hoc Networking & Computing, pages 201–212, 2003.

    Google Scholar 

  14. K. Whitehouse, C. Karlof, and D. Culler. A practical evaluation of radio signal strength for ranging-based localization. SIGMOBILE Mobile Computing and Communications Review, 11(1):41–52, 2007.

    Article  Google Scholar 

  15. R. Reghelin and A. A. Fröhlich. A decentralized location system for sensor networks using cooperative calibration and heuristics. In MSWiM 2006: Proceedings of the 9th ACM International Symposium on Modeling Analysis and Simulation of Wireless and Mobile Systems, pages 139–146, 2006.

    Google Scholar 

  16. H. Lim, L.-C. Kung, J. C. Hou, and H. Luo. Zero-configuration, robust indoor localization: Theory and experimentation. INFOCOM 2006: 25th IEEE International Conference on Computer Communications, pages 1–12, April 2006.

    Google Scholar 

  17. R. Peng and M. L. Sichitiu. Probabilistic localization for outdoor wireless sensor networks. SIGMOBILE Mobile Computing and Communications Review, 11(1):53–64, 2007.

    Article  Google Scholar 

  18. X. Cheng, A. Thaeler, G. Xue, and D. Chen. TPS: a time-based positioning scheme for outdoor wireless sensor networks. INFOCOM 2004: 23rd AnnualJoint Conference of the IEEE Computer and Communications Societies, 4:2685–2696, 2004.

    Google Scholar 

  19. J. Zhang, T. Yan, J. A. Stankovi, and S. H. Son. Thunder: towards practical, zero cost acoustic localization for outdoor wireless sensor networks. SIGMOBILE Mobile Computing and Communications Review, 11(1):15–28, 2007.

    Article  Google Scholar 

  20. M. Broxton, J. Lifton, and J. A. Paradiso. Localization on the pushpin computing sensor network using spectral graph drawing and mesh relaxation. SIGMOBILE Mobile Computing and Communications Review, 10(1):1–12, 2006.

    Article  Google Scholar 

  21. A. Savvides, C.-C. Han, and M. B. Strivastava. Dynamic fine-grained localization in ad-hoc networks of sensors. In MobiCom 2001: the 7th Annual International Conference on Mobile Computing and Networking, pages 166–179, 2001.

    Google Scholar 

  22. M. Youssef, A. Youssef, C. Rieger, U. Shankar, and A. Agrawala. PinPoint: An asynchronous time-based location determination system. In MobiSys 2006: the 4th International Conference on Mobile Systems, Applications and Services, pages 165–176, 2006.

    Google Scholar 

  23. T. Eren, O. Goldenberg, W. Whiteley, Y. Yang, A. Morse, B. Anderson, and P. Belhumeur. Rigidity, computation, and randomization in network localization. INFOCOM 2004: The 23rd AnnualJoint Conference of the IEEE Computer and Communications Societies, 4: pages 2673–2684, 2004.

    Google Scholar 

  24. J. Aspnes, D. Goldenberg, and Y. R. Yang. On the computational complexity of sensor network localization. In The 1st International Workshop on Algorithmic Aspects of Wireless Sensor Networks, pages 32–44, 2004.

    Google Scholar 

  25. A. M.-C. So and Y. Ye. Theory of semidefinite programming for sensor network localization. Mathmatical Programming, 109(2):367–384, 2007.

    Article  MATH  MathSciNet  Google Scholar 

  26. D. Niculescu and B. Nath. Ad hoc positioning system (APS) using AOA. INFOCOM 2003: The 22nd Annual Joint Conference of the IEEE Computer and Communications Societies, 3:1734–1743, 2003.

    Google Scholar 

  27. D. Niculescu and B. Nath. Dv based positioning in ad hoc networks. Telecommunication Systems, 22(1–4):267–280, 2003.

    Article  Google Scholar 

  28. Y. Zhang and L. Cheng. PLACE: protocol for location and coordinate estimation: A wireless sensor network approach. Computing Network, 46(5):679–693, 2004.

    Article  Google Scholar 

  29. K. Chintalapudi, A. Dhariwal, R. Govindan, and G. Sukhatme. Ad-hoc localization using ranging and sectoring. INFOCOM 2004: The 23rd AnnualJoint Conference of the IEEE Computer and Communications Societies, 4:2662–2672, 2004.

    Google Scholar 

  30. A. Savvides, H. Park, and M. B. Srivastava. The bits and flops of the n-hop multilateration primitive for node localization problems. In WSNA 2002: The 1st ACM International Workshop on Wireless Sensor Networks and Applications, pages 112–121, ACM, New York, NY, 2002.

    Google Scholar 

  31. L. Doherty, K. Pister, and L. E. Ghaoui. Convex position estimation in wireless sensor networks. INFOCOM 2001: The 20th Annual Joint Conference of the IEEE Computer and Communications Societies, 3:1655–1663, 2001.

    Google Scholar 

  32. P. Biswas, T.-C. Lian, T.-C. Wang, and Y. Ye. Semidefinite programming based algorithms for sensor network localization. ACM Transaction on Sensor Networks, 2(2):188–220, 2006.

    Article  Google Scholar 

  33. X. Ji and H. Zha. Sensor positioning in wireless ad-hoc sensor networks using multidimensional scaling. INFOCOM 2004: The 23rd AnnualJoint Conference of the IEEE Computer and Communications Societies, 4: 2652–2661, 2004.

    Google Scholar 

  34. D. Moore, J. Leonard, D. Rus, and S. Teller. Robust distributed network localization with noisy range measurements. SenSys 2004: The 2nd International Conference on Embedded Networked Sensor Systems, pages 50–61, 2004.

    Google Scholar 

  35. P. Stoica and K. Sharman. Maximum likelihood methods for direction-of-arrival estimation, IEEE Transactions on Acoustics Speech and Signal Processing, 38(7):1132–1143, 1990.

    Article  MATH  Google Scholar 

  36. N. B. Priyantha, A. Chakraborty, and H. Balakrishnan. The cricket location-support system, MobiCom 2000: The 6th Annual ACM International Conference on Mobile Computing and Networking, 2000.

    Google Scholar 

  37. J. Bruck, J. Gao, and A. A. Jiang. Localization and routing in sensor networks by local angle information. MobiHoc 2005: The 6th ACM International Symposium on Mobile Ad Hoc Networking and Computing, pages 181–192, 2005.

    Google Scholar 

  38. M. Bădoiu, E. D. Demaine, M. T. Hajiaghayi, and P. Indyk. Low-dimensional embedding with extra information. SCG 2004: The 20th Annual Symposium on Computational Geometry, pages 320–329, 2004.

    Google Scholar 

  39. O.-H. Kwon and H.-J. Song. Localization through map stitching in wireless sensor networks. IEEE Transactions on Parallel and Distributed Systems, 19(1):93–105, 2008.

    Article  MathSciNet  Google Scholar 

  40. R. Iyengar and B. Sikdar. Scalable and distributed GPS free positioning for sensor networks. ICC 2003: IEEE International Conference on Communications, 1:338–342, 2003.

    Article  Google Scholar 

  41. H. Chan, M. Luk, and A. Perrig. Using clustering information for sensor network localization. DCOSS 2005: IEEE Conference on Distributed Computing in Sensor Systems, 2005.

    Google Scholar 

  42. J. A. Costa, N. Patwari, and A. O. H. Iii. Distributed weighted-multidimensional scaling for node localization in sensor networks, ACM Transactions Sensor Networks, 2:39–64, 2006.

    Article  Google Scholar 

  43. J. Liu, Y. Zhang, and F. Zhao, Robust distributed node localization with error management. MobiHoc 2006: The 7th ACM International Symposium on Mobile Ad Hoc Networking and Computing, pages 250–261, 2006.

    Google Scholar 

  44. S. Nikoletseas and P. Spirakis. Efficient sensor network design for continuous monitoring of moving objects. Theoretical Computer Science, 402(1):56–66, 2008.

    Article  MATH  MathSciNet  Google Scholar 

  45. M. L. Sichitiu and V. Ramadurai. Localization of wireless sensor networks with a mobile beacon. IEEE International Conference on Mobile Ad-hoc and Sensor Systems, pages 174–183, 2004.

    Google Scholar 

  46. A. Galstyan, B. Krishnamachari, K. Lerman, and S. Pattem. Distributed online localization in sensor networks using a moving target. IPSN 2004: The 3rd International Symposium on Information Processing in Sensor Networks, pages 61–70, 2004.

    Google Scholar 

  47. K.-F. Ssu, C.-H. Ou, and H. Jiau. Localization with mobile anchor points in wireless sensor networks, IEEE Transactions on Vehicular Technology, 54(3):1187–1197, 2005.

    Article  Google Scholar 

  48. P. Bahl and V. N. Padmanabhan. RADAR: An in-building RF-based user location and tracking system. INFOCOM 2000: The 19th IEEE International Conference on Computer Communications, pages 775–784, 2000.

    Google Scholar 

  49. X. Nguyen, M. I. Jordan, and B. Sinopoli. A kernel-based learning approach to ad hoc sensor network localization. ACM Transactions Sensor Networks, 1(1):134–152, 2005.

    Article  Google Scholar 

  50. E. T. Ihler, J. W. Fisher, O. L. Moses, and A. S. Willsky. Nonparametric belief propagation for self-localization of sensor networks. IEEE Journal on Selected Areas Communications, 23:809–819, 2005.

    Article  Google Scholar 

  51. C. Taylor, A. Rahimi, J. Bachrach, H. Shrobe, and A. Grue. Simultaneous localization, calibration, and tracking in an ad hoc sensor network. IPSN 2006: The 5th International Conference on Information Processing in Sensor Networks, pages 27–33, 2006.

    Google Scholar 

  52. D. Fox, J. Hightower, L. Liao, D. Schulz, and G. Borriello. Bayesian filtering for location estimation. IEEE Pervasive Computing, 2(3):24–33, 2003.

    Article  Google Scholar 

  53. L. Hu and D. Evans. Localization for mobile sensor networks. MobiCom 2004: The 10th Annual International Conference on Mobile Computing and Networking, pages 45–57, 2004.

    Google Scholar 

  54. L. Zhang, Q. Cheng, Y. Wang, and S. Zeadally. Landscape: a high performance distributed positioning scheme for outdoor sensor networks. WiMob 2005: IEEE International Conference on Wireless and Mobile Computing, Networking and Communications, 3:430–437, 2005.

    Article  Google Scholar 

  55. R. Peng and M. L. Sichitiu. Probabilistic localization for outdoor wireless sensor networks. SIGMOBILE Mobile Computing Communication Review, 11(1):53–64, 2007.

    Article  Google Scholar 

  56. D. Madigan, E. Einahrawy, R. P. Martin, W. H. Ju, P. Krishnan, and A. S. Krishnakumar. Bayesian indoor positioning systems. INFOCOM 2005: The 24th Annual Joint Conference of the IEEE Computer and Communications Societies, 2:1217–1227, 2005.

    Article  Google Scholar 

  57. A. Cerpa, J. L. Wong, L. Kuang, M. Potkonjak, and D. Estrin. Statistical model of lossy links in wireless sensor networks. IPSN 2005: The 4th International Symposium on Information Processing in Sensor Networks, 2005.

    Google Scholar 

  58. S. Slijepcevic, S. Megerian, and M. Potkonjak. Location errors in wireless embedded sensor networks: sources, models, and effects on applications. SIGMOBILE Mobile Computing Communications Review, 6(3):67–78, 2002.

    Article  Google Scholar 

  59. H. A. Oliveira, E. F. Nakamura, A. A. F. Loureiro, and A. Boukerche. Error analysis of localization systems for sensor networks, GIS 2005: The 13th Annual ACM International Workshop on Geographic Information Systems, pages 71–78, 2005.

    Google Scholar 

  60. A. Savvides, W. Garber, R. Moses, and M. Srivastava. An analysis of error inducing parameters in multihop sensor node localization. IEEE Transactions Mobile Computing, 4(6):567–577, Nov.-Dec. 2005.

    Article  Google Scholar 

  61. K. Whitehouse, C. Karlof, A. Woo, F. Jiang, and D. Culler. The effects of ranging noise on multihop localization: an empirical study. IPSN 2005: The 4th International Symposium on Information Processing in Sensor Networks, pages 73–80, 2005.

    Google Scholar 

  62. N. Patwari, I. A.O. Hero, M. Perkins, N. Correal, and R. O’Dea. Relative location estimation in wireless sensor networks. IEEE Trans. Signal Processing , 51(8):2137–2148, 2003.

    Article  Google Scholar 

  63. C. Chang and A. Sahai. Estimation bounds for localization. SECON 2004: The 1st IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks, pages 415–424, 2004.

    Google Scholar 

  64. S. Venkatesh and R. M. Buehrer. Multiple-access insights from bounds on sensor localization. Pervasive Mobile Computing, 4(1): 33–61, 2008.

    Article  Google Scholar 

  65. N. Bulusu, J. Heidemann, D. Estrin, and T. Tran. Self-configuring localization systems: Design and experimental evaluation. Transactions on Embedded Computing Systems, 3(1):24–60, 2004.

    Article  Google Scholar 

  66. K. Yedavalli, B. Krishnamachari, S. Ravula, and B. Srinivasan. Ecolocation: A sequence based technique for RF localization in wireless sensor networks. IPSN 2005: The 4th International Symposium on Information Processing in Sensor Networks, pages 285–292, 2005.

    Google Scholar 

  67. K. Sreenath, F. L. Lewis, and D. O. Popa. Simultaneous adaptive localization of a wireless sensor network. SIGMOBILE Mobile Computing Communication Review, 11(2):14–28, 2007.

    Article  Google Scholar 

  68. A. Y. Teymorian, W. Cheng, L. Ma, X. Cheng, X. Lu, and Z. Lu. 3d underwater sensor network localization. IEEE Transactions. Mobile Computing., 8:1610–1621, 2009.

    Article  Google Scholar 

  69. H. S. Abdelsalam and S. Olariu. A 3d-localization and terrain modeling technique for wireless sensor networks. In FOWANC 2009: The 2nd ACM International Workshop on Foundations of Wireless Ad Hoc and Sensor Networking and Computing. ACM, New York, NY, pages 37–46, 2009.

    Google Scholar 

  70. Z. Li, W. Trappe, Y. Zhang, and B. Nath. Robust statistical methods for securing wireless localization in sensor networks. IPSN 2005: The 4th International Symposium on Information Processing in Sensor Networks, pages 91–98, 2005.

    Google Scholar 

  71. L. Lazos, R. Poovendran, and S. Čapkun. ROPE: robust position estimation in wireless sensor networks. IPSN 2005: The 4th International Symposium on Information Processing in Sensor Networks, 2005.

    Google Scholar 

  72. M. Shao, Y. Yang, S. Zhu, and G. Cao. Towards statistically strong source anonymity for sensor networks. In INFOCOM 2008: The 27th IEEE International Conference on Computer Communications, pages 51–55, 2008.

    Google Scholar 

  73. Y. Jian, S. Chen, Z. Zhang, and L. Zhang. Protecting receiver-location privacy in wireless sensor networks. In INFOCOM 2007: The 26th IEEE International Conference on Computer Communications, pages 1955–1963, 2007.

    Google Scholar 

Download references

Acknowledgement

This work is partially supported by an EADS grant and NSF grants CNS-0916221 and CNS-0721951 and a Research I grant.

Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Center for Research in Wireless Mobility and Networking (CReWMaN), University of Texas at Arlington, Arlington, TX, 76019, USA

    Sajal K. Das & Jing Wang

  2. Department of Computer Science and Engineering, Indian Institute of Technology, Kanpur, India

    R.K. Ghosh

  3. EADS, Innovation Works, Munich, Germany

    Rupert Reiger

Authors
  1. Sajal K. Das
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jing Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. R.K. Ghosh
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Rupert Reiger
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sajal K. Das .

Editor information

Editors and Affiliations

  1. Computer Technology Institute, N. Kazantzaki Street 1, Rion, Patras, 265 04, Greece

    Sotiris Nikoletseas

  2. Centre Universitaire d'Informatique, Université de Genève, rte de Drize 7, Carouge, 1227, Switzerland

    José D.P. Rolim

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Das, S.K., Wang, J., Ghosh, R., Reiger, R. (2011). Algorithmic Aspects of Sensor Localization. In: Nikoletseas, S., Rolim, J. (eds) Theoretical Aspects of Distributed Computing in Sensor Networks. Monographs in Theoretical Computer Science. An EATCS Series. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14849-1_9

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-14849-1_9

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-14848-4

  • Online ISBN: 978-3-642-14849-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation