http://iet.metastore.ingenta.com
1887

Dead reckoning localisation technique for mobile wireless sensor networks

Dead reckoning localisation technique for mobile wireless sensor networks

For access to this article, please select a purchase option:

Buy article PDF
£12.50
(plus tax if applicable)
Buy Knowledge Pack
10 articles for £75.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
 
IET Wireless Sensor Systems — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

Localisation in wireless sensor networks (WSNs) not only provides a node with its geographical location but also a basic requirement for other applications such as geographical routing. Although a rich literature is available for localisation in static WSN, not enough work is done for mobile WSNs, owing to the complexity because of node mobility. Most of the existing techniques for localisation in mobile WSNs use Monte Carlo localisation (MCL), which is not only time consuming but also memory intensive. They, consider either the unknown nodes or anchor nodes to be static. In this study, the authors propose a technique called dead reckoning localisation for mobile WSNs (DRLMSN). In the proposed technique all nodes (unknown nodes as well as anchor nodes) are mobile. Localisation in DRLMSN is done at discrete time intervals called checkpoints. Unknown nodes are localised for the first time using three anchor nodes. For their subsequent localisations, only two anchor nodes are used. The proposed technique estimates two possible locations of a node using Bézout's theorem. A dead reckoning approach is used to select one of the two estimated locations. The authors have evaluated DRLMSN through simulation using Castalia simulator, and is compared with a similar technique called received signal strength-MCL proposed by Wang and Zhu (2008).

References

    1. 1)
    2. 2)
      • 2. Caruso, A., Chessa, S., De, S., Urpi, R.: ‘GPS free coordinate assignment and routing in wireless sensor networks’. IEEE INFOCOM, 2005, pp. 150160.
    3. 3)
      • 3. Dopico, N.I., Haro, B.B., Macua, S.V., Belanovic, P., Zazo, S.: ‘Improved animal tracking algorithms using distributed Kalman-based filters’. European Wireless, 2011, pp. 631638..
    4. 4)
    5. 5)
    6. 6)
    7. 7)
      • 7. Hu, L., Evans, D.: ‘Localization for mobile sensor networks’. Proc.10th annual Int. Conf. Mobile Computing and Networking, MobiCom ‘04, Philadelphia, PA, USA, 2004, pp. 4557.
    8. 8)
      • 8. Liu, Y., Yang, Z.: ‘Localization for mobile networks’, inLocation, localization, and localizability’, (Springer, 2011, 1st edn.), pp. 97109.
    9. 9)
      • 9. Galstyan, A., Krishnamachari, B., Lerman, K., Pattem, S.: ‘Distributed online localization in sensor networks using a moving target’. Third Int. Symp. Information Processing in Sensor Networks (IPSN), ISPN 04, 26–27 April 2004, pp. 6170.
    10. 10)
    11. 11)
    12. 12)
      • 12. Jiang, J., Han, G., Xu, H., Shu, L., Guizani, M.: ‘LMAT: localization with a mobile anchor node based on trilateration in wireless sensor networks’. Global Telecommunications Conf. (GLOBECOM 2011), 2011 IEEE, 5–9 December 2011, pp. 16.
    13. 13)
      • 13. Bergamo, P., Mazzimi, G.: ‘Localization in sensor networks with fading and mobility’. 13th IEEE Int. Symp. Personal, Indoor and Mobile Radio Communications, 15–18 September 2002, vol. 2, pp. 750754.
    14. 14)
      • 14. de Oliveira, L.L., Martins, J.B., Dessbesell, G., Monteiro, J.: ‘CentroidM: a centroid-based localization algorithm for mobile sensor networks’. Proc. 23rd Symp. Integrated Circuits and System Design, SBCCI ‘10, New York, NY, USA, 2010, pp. 204209.
    15. 15)
    16. 16)
    17. 17)
      • 17. Rad, H.J., Amar, A., Leus, G.: ‘Cooperative mobile network localization via subspace tracking’. IEEE Int. Conf. Acoustics, Speech and Signal Processing, ICASSP ‘11, 2011, pp. 26122615.
    18. 18)
    19. 19)
    20. 20)
      • 20. Rashid, H.: ‘Localization in wireless sensor networks’. Master's thesis, National Institute of Technology Rourkela, India, 2013.
    21. 21)
    22. 22)
      • 22. Watkins, T.: ‘Bézout's Theorem’. Available from http://www.sjsu.edu/faculty/watkins/bezout.htm.
    23. 23)
      • 23. Akyildiz, I.F., Vuran, M.C.: ‘Localization’, inWireless sensor networks’, (John Wiley and Sons Ltd, 2010), pp. 265284.
    24. 24)
    25. 25)
    26. 26)
    27. 27)
    28. 28)
      • 28. Li, X., Shi, H., Shang, Y.: ‘A partial-range-aware localization algorithm for ad-hoc wireless sensor networks’. Proc. 29th Annual IEEE Int. Conf. Local Computer Networks, LCN ‘04, 16–18 November 2004, pp. 7783.
    29. 29)
    30. 30)
      • 30. He, T., Huang, C., Blum, B., Stankovic, J., Abdelzaher, T.: ‘Range free localization schemes in large scale sensor networks’. Proc. Ninth Annual Int. Conf. Mobile Computing and Networking, MobiCom ‘03, 14–19 September 2003, pp. 8195.
    31. 31)
      • 31. Tilak, S., Kolar, V., Abu-Ghazaleh, N.B., Kang, K.D.: ‘Dynamic localization control for mobile sensor networks’. 24th IEEE Int. Conf. Performance, Computing, and Communications, IPCC ‘05, 7–9 April 2005, pp. 587592.
    32. 32)
    33. 33)
      • 33. Rudafshani, M., Datta, S.: ‘Localization in wireless sensor networks’. Proc. Sixth Int. Conf. Information Processing in Sensor Networks, ISPN ‘07, Cambridge, MA, USA, 2007, pp. 5160.
    34. 34)
      • 34. Shigeng, Z., Cao, J., Lijun, C., Daoxu, C.: ‘Locating nodes in mobile sensor networks more accurately and faster’. Fifth Annual IEEE Communications Society Conf. Sensor, Mesh and Ad Hoc Communications and Networks, SECON ‘08, 16–20 June 2008, pp. 3745.
    35. 35)
      • 35. Roy, R.R.: ‘Reference point group mobility’, in ‘Handbook of mobile ad hoc networks for mobility models’ (Springer, 2011), pp. 637670.
    36. 36)
      • 36. Boulis, A.: ‘Castalia: a simulator for wireless sensor networks and body area networks’ (NICTA: National ICT Australia, 2011).
    37. 37)
      • 37. Schindelhauer, C.: ‘Mobility in wireless networks’. Proc. 32nd Annual Conf. Current Trends in Theory and Practice of Computer Science, SOFSEM ‘06, Berlin, Heidelberg, 2006, pp. 100116.
    38. 38)
      • 38. Royer, E.M., Michael Melliar-Smithy, P., Moser, L.E.: ‘An analysis of the optimum node density for ad hoc mobile networks’. IEEE Int. Conf. Communications, ICC, 2001, vol. 3, pp. 857861.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-wss.2014.0043
Loading

Related content

content/journals/10.1049/iet-wss.2014.0043
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address