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2018 | OriginalPaper | Buchkapitel

Wireless Sensor Network Localization Approach Based on Bayesian MDS

verfasst von : Zhongmin Pei

Erschienen in: Geo-Spatial Knowledge and Intelligence

Verlag: Springer Singapore

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Abstract

The aim of wireless sensor networks (WSNs) are to perceive, collect and process the information of sensor nodes within the coverage of the network. As a bridge between the physical world and the digital one, WSNs have widely been applied in many fields. One of the key issues for most applications is to know the location of sensor nodes. Though localization algorithms based on multidimensional scaling (MDS), which only need several anchor nodes, have been proven to be robust with respect to range-based implementations, these methods are sensitive inaccuracy range measure. This article proposes a novel localization algorithm based on Bayesian MDS, named as MDS-MAP(P, B), where P and B denote the use of patching of local maps and Bayesian MDS, respectively. Experimental results in real-world systems show that our method is more robust and efficient.

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Akyildiz, I.F., Su, W., Sankarasubramaniam, Y., Cayirci, E.: Wireless sensor networks: a survey. Comput. Netw. 38(4), 393–422 (2002)CrossRef

Onur, E., Ersoy, C., Delic, H., Akarun, L.: Surveillance wireless sensor networks: deployment quality analysis. IEEE Netw. 21(6), 48–53 (2007)CrossRef

Wu, H., Zhang, Q., Nie, S., Sun, W., Guan, X.: An energy distribution and optimization algorithm in wireless sensor networks for maritime search and rescue. Int. J. Distrib. Sens. Netw. 2013, 1–8 (2013)CrossRef

Oliveira, L.M.L., Rodrigues, J.J.P.C.: Wireless sensor networks: a survey on en environment monitoring. J. Commun. 6(2), 143–151 (2011)CrossRef

Pei, Z., Deng, Z., Xu, S., Xu, X.: Archor-free localization method for mobile target sin coal mine wireless sensor networks. Sensors 9(4), 2836–2850 (2009)CrossRef

An, X., Xu, S., Chen, J., Zhang, Y.: Distributed risk aversion parameter estimation for first-price auction in sensor networks. Int. J. Distrib. Sens. Netw. 2013, 1–9 (2013)CrossRef

Pei, Z., Yibin, L., Xu, S.: A fast localization algorithm for large-scale wireless sensor networks. J. China Univ. Min. Technol. 42(2), 314–319 (2013)

Xu, S., Qiao, X., Zhu, L., Zhang, Y., Li, L.: Fast but not bad initial configuration for metric multidimensional scaling. J. Inf. Comput. Sci. 9(2), 257–265 (2012)

Han, G., Xu, H., Duong, T.Q., Jiang, J., Hara, T.: Localization algorithms of wireless sensor networks: a survey. Telecommun. Syst. 52(4), 2419–2436 (2013)CrossRef

10.

Uckelmann, D., Harrison, M., Michahelles, F. (eds.): Architecting the Internet of Things. Springer, New York (2011)

11.

Pei, Z., Deng, Z., Xu, S., Xu, X.: A new localization method for wireless sensor network n-node based on n-best rank sequence. ACTA Automatica China 36(2), 119–207 (2010)

12.

Girod, L., Bychkovskiy, V., Elson, J., Estrin, D.: Locating tiny sensor in time and space: a case study. In: Proceedings of the 2002 IEEE International Conference on Computer Design: VLSI in Computers and Processors, Los Alamitos, CA, USA, pp. 214–219. IEEE Computer Society (2002)

13.

Harter, A., Hopper, A., Steggles, P., Ward, A., Webster, P.: The anatomy of a context-aware application. In: Proceedings of the 5th Annual ACM/IEEE International Conference on Mobile Computing and Networking, New York, NY, USA, pp. 59–68. ACM (1999)

14.

Girod, L., Estrin, D.: Robust range estimation using acoustic and multimodal sensing. In: Proceedings of the 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems, vol. 3, Los Alamitos, CA, USA, pp. 1312–1320. IEEE Computer Society (2001)

15.

Niculescu, D., Nath, B.: Ad hoc positioning system (APS) using AOA. In: Proceedings of the 22nd Annual Joint Conference of the IEEE Computer and Communications, vol. 3, Los Alamitos, CA, USA, pp. 1734–1743. IEEE Computer Society (2003)

16.

Cox, T.F., Cox, M.A.A. (eds.): Multidimensional Scaling, 2nd edn. Chapman & Hall/CRC, Boca Raton (2001)MATH

17.

Borg, I., Groenen, P.J.F. (eds.): Modern Multidimensional Scaling: Theory and Application, 2nd edn. Spinger, New York (2005)MATH

18.

Shang, Y., Ruml, W., Zhang, Y., Fromherz, M.P.J.: Localization from mere connectivity. In: Proceedings of the 4th ACM International Symposium on Mobile Ad Hoc Networking & Computing, New York, NY, USA, pp. 201–212. ACM (2003)

19.

Shang, Y., Ruml, W.: Improved MDS-based localization. In: Proceedings of the 23rd Annual Joint Conference of the IEEE Computer and Communications Societies, vol. 4, Los Alamitos, CA, USA, pp. 2640– 2651. IEEE Computer Society (2004)

20.

Vivekanandan, V., Wong, V.W.S.: Ordinal MDS-based localization for wireless sensor networks. Int. J. Sens. Netw. 1(3/4), 169–178 (2006)CrossRef

21.

Oh, M.S., Raftery, A.E.: Bayesian multidimensional scaling and choice of dimension. J. Am. Stat. Assoc. 96(455), 1031–1044 (2001)MathSciNetCrossRef

22.

Yedavalli, K., Krishnamachari, B.: Sequence-based localization in wireless sensor networks. IEEE Trans. Mob. Comput. 7(1), 81–94 (2008)CrossRef

23.

Dijkstra, E.W.: A note on two problems in connexion with graphs. Numer. Math. 1(1), 269–271 (1959)MathSciNetCrossRef

24.

Andrieu, C., de Freitas, N., Doucet, A., Jordan, M.I.: An introduction to MCMC for machine learning. Mach. Learn. 50(1–2), 5–43 (2003)CrossRef

Titel: Wireless Sensor Network Localization Approach Based on Bayesian MDS
verfasst von: Zhongmin Pei
Verlag: Springer Singapore
Buch: Geo-Spatial Knowledge and Intelligence
Print ISBN: 978-981-13-0895-6

Electronic ISBN: 978-981-13-0896-3

Copyright-Jahr: 2018
DOI: https://doi.org/10.1007/978-981-13-0896-3_69

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