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Localized Approximation Method Using Inertial Compensation in WSNs

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New Challenges for Intelligent Information and Database Systems

Part of the book series: Studies in Computational Intelligence ((SCI,volume 351))

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Abstract

Sensor nodes in a wireless sensor network establish a network based on location information, set a communication path to the sink for data collection, and have the characteristic of limited hardware resources such as battery, data processing capacity, and memory. The method of estimating location information using GPS is convenient, but it is relatively inefficient because additional costs accrue depending on the size of space. In the past, several approaches including range-based and range-free have been proposed to calculate positions for randomly deployed sensor nodes. Most of them use some special nodes called anchor nodes, which are assumed to know their own locations. Other sensors compute their locations based on the information provided by these anchor nodes. This paper uses a single mobile anchor node to move in the sensing field and broadcast its current position periodically. We provide a weighted centroid localization algorithm that uses coefficients, which are decided by the influence of mobile anchor node to unknown nodes, to prompt localization accuracy. In addition, this study lowered the error rate resulting from difference in response time by adding reliability for calculating and compensating detailed location information using inertia.

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References

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

    Article  Google Scholar 

  2. Hu, L., Evans, D.: Localization for mobile sensor networks. In: Proc. of ACM MobiCom (2004)

    Google Scholar 

  3. Song, C.W., Ma, J.L., Lee, J.H., Chung, K.Y., Rim, K.W.: Localization Accuracy Improved Methods Based on Adaptive Weighted Centroid Localization Algorithm in Wireless Sensor Networks. International Journal of Computer Science and Information Security 8(8), 284–288 (2010)

    Google Scholar 

  4. Laurendeau, C., Barbeau, M.: Centroid localization of uncooperative nodes in wireless networks using a relative span weighting method. EURASIP J. Wirel. Commun. Netw. (2010)

    Google Scholar 

  5. Nagpal, R., Shrobe, H.E., Bachrach, J.: Organizing a global coordinate system from local information on an ad hoc sensor network. In: Zhao, F., Guibas, L.J. (eds.) IPSN 2003. LNCS, vol. 2634, pp. 333–348. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  6. Niculescu, D., Nath, B.: DV based positioning in ad hoc networks. Journal of Telecommunication Systems 22(4), 267–280 (2003)

    Article  Google Scholar 

  7. Kim, Y.C., Kim, Y.J., Chang, J.W.: Distributed Grid Scheme using S-GRID for Location Information Management of a Large Number of Moving Objects. Journal of Korea Spatial Information System Society 10(4), 11–19 (2008)

    Google Scholar 

  8. Lee, Y.K., Jung, Y.J., Ryu, K.H.: Design and Implementation of a System for Environmental Monitoring Sensor Network. In: Proc. Conf. APWeb/WAIM Workshop on DataBase Management and Application over Networks, pp. 223–228 (2008)

    Google Scholar 

  9. Hammad, M.A., Aref, W.G., Elmagarmid, A.K.: Stream window join: Tracking moving objects in sensor network databases. In: SSDBM (2003)

    Google Scholar 

  10. Niculescu, D., Nath, B.: Position and orientation in ad hoc networks. Ad hoc Networks 2(2), 133–151 (2002)

    Article  Google Scholar 

  11. Chen, Y., Pan, Q., Liang, Y., Hu, Z.: AWCL: Adaptive weighted centroid target localization algorithm based on RSSI in WSN. Proc. IEEE ICCSIT 9, 9–11 (2010)

    Google Scholar 

  12. Wang, J., Urriza, P., Han, Y., Cabrić, D.: Performance analysis of weighted centroid algorithm for primary user localization in cognitive radio networks. In: Proc. ACSSC, Pacific Grove, pp. 7–10 (2010)

    Google Scholar 

  13. Titterton, D.H., Weston, J.L.: Strapdown Inertial Navigation Technology. Peter Pegerinus (1997)

    Google Scholar 

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© 2011 Springer-Verlag Berlin Heidelberg

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Song, C., Chung, K., Jung, J.J., Rim, K., Lee, J. (2011). Localized Approximation Method Using Inertial Compensation in WSNs. In: Nguyen, N.T., Trawiński, B., Jung, J.J. (eds) New Challenges for Intelligent Information and Database Systems. Studies in Computational Intelligence, vol 351. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19953-0_25

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  • DOI: https://doi.org/10.1007/978-3-642-19953-0_25

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-19952-3

  • Online ISBN: 978-3-642-19953-0

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