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Monte Carlo localization of wireless sensor networks with a single mobile beacon

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Abstract

One of the most important tasks in sensor networks is to determine the physical location of sensory nodes as they may not all be equipped with GPS receivers. In this paper we propose a localization method for wireless sensor networks (WSNs) using a single mobile beacon. The sensor locations are maintained as probability distributions that are sequentially updated using Monte Carlo sampling as the mobile beacon moves over the deployment area. Our method relieves much of the localization tasks from the less powerful sensor nodes themselves and relies on the more powerful beacon to perform the calculation. We discuss the Monte Carlo sampling steps in the context of the localization using a single beacon for various types of observations such as ranging, Angle of Arrival (AoA), connectivity and combinations of those. We also discuss the communication protocol that relays the observation data to the beacon and the localization result back to the sensors. We consider security issues in the localization process and the necessary steps to guard against the scenario in which a small number of sensors are compromised. Our simulation shows that our method is able to achieve less than 50% localization error and over 80% coverage with a very sparse network of degree less than 4 while achieving significantly better results if network connectivity increases.

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References

  1. Ahmed, A. A., Shi, H., & Shang, Y. (2005). SHARP: A new approach to relative localization in wireless sensor networks. In Proceedings ICDCS Workshops, pp. 892–898.

  2. Biswas, P., & Ye, Y. (2004). Semidefinite programming for ad hoc wireless sensor network localization. In Proceedings Third International Symposium on Information Processing in Sensor Networks, pp. 46–54.

  3. Bulusu, N., Heidemann, J., & Estrin, D. (2000). GPS-less low cost outdoor localization for very small devices. IEEE Personal Communications Magazine, 7(5), 28–34.

    Article  Google Scholar 

  4. Chintalapudi, K., Govindan, R., Sukhatme, G., & Dhariwal, A. (2004). Ad-hoc localization using ranging and sectoring. In Proceedings IEEE INFOCOM, April, Hong Kong, China.

  5. Galstyan, A., Krishnamachari, B., Lerman, K., & Pattem, S. (2004). Distributed online localization in sensor networks using a moving target. In Proceedings IPSN, pp. 61–70.

  6. He, T., Huang, C., Blum, B. M., Stankovic, J. A., & Abdelzaher, T. F. (2003). Range-free localization schemes in large scale sensor networks. In Proceedings ACM/IEEE MOBICOM.

  7. Hu, Y.-C., Perrig, A., & Johnson, D. (2003). Packet leashes: A defense against wormhole attacks in wireless ad hoc networks. In Proceedings IEEE INFOCOM, April.

  8. Huang, R., & Záruba, G. V. (2007) Incorporating multiple sensory data for mobile ad hoc networks localization. IEEE Transactions on Mobile Computing, 6(9), 1090–1104.

    Google Scholar 

  9. Jiang, X., & Camp, T. (2002). Review of geocasting protocols for a mobile ad hoc network. In Proceedings Grace Hopper Celebration.

  10. Ko, Y., & Vaidya, N. H. (1998). Location-aided routing (LAR) in mobile ad hoc networks. In Proceedings ACM/IEEE MOBICOM, Dallas, TX.

  11. Ko, Y., & Vaidya, N. (1999). Geocasting in mobile ad hoc betworks: location-based multicast algorithms. In Proceedings IEEE Workshop on Mobile Computing Systems and Applications.

  12. Kuhn, F., Wattenhofer, R., Zhang, Y., & Zollinger, A. (2003). Geometric ad-hoc routing: Of theory and practice. In Proceedings PODC, pp. 63–72.

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

    Article  MATH  Google Scholar 

  14. Larsson, E. G. (2004). Cramer-Rao bound analysis of distributed positioning in sensor networks. IEEE Signal Processing Letters, 11(3), 334–337.

    Article  Google Scholar 

  15. Liao, W.-H., Tseng, Y.-C., & Sheu, J.-P. (2001). GRID: A fully location-aware routing protocol for mobile ad hoc networks. Telecommunication Systems, 18(1), 37–60.

    Article  MATH  Google Scholar 

  16. Liao, W.-H., Tseng, Y.-C., Lo, K.-L., & Sheu, J.-P. (2000). Geogrid: A geocasting protocol for mobile ad hoc networks based on grid. Journal of Internet Technology, 1(2), 23–32.

    Google Scholar 

  17. Mauve, M., Fuler, H., Widmer, J., & Lang, T. (2003). Position-based multicast routing for mobile ad-hoc networks, Technical report TR-03-004. Department of Computer Science, University of Mannheim.

  18. Niculescu, D., & Nath, B. (2001). Ad hoc positioning system (APS). In Proceedings IEEE GLOBECOM, San Antonio.

  19. Niculescu, D., & Nath, B. (2004). VOR base stations for indoor 802.11 positioning. In Proceedings 10th Annual International Conference on Mobile Computing and Networking.

  20. Niculescu, D., & Nath, B. (2003). DV based positioning in ad hoc networks. Telecommunication Systems, 22(1–4), 267–280.

    Article  Google Scholar 

  21. Niculescu, D., & Nath, B. (2003). Ad hoc positioning system (APS) using AoA. In Proceedings IEEE INFOCOM, San Francisco.

  22. Peng, R., & Sichitiu, M. L. (2005). Robust, probabilistic, constraint-based localization for wireless sensor networks. In Proceedings Second Annual IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks, September, Santa Clara, CA.

  23. Savarese, C., Rabay, J., & Langendoen, K. (2002). Robust positioning algorithms for distributed ad-hoc wireless sensor networks. In Proceedings USENIX Technical Annual Conference, June, Monterey, CA.

  24. Sichitiu, M. L., & Ramadurai, V. (2004). Localization of wireless sensor networks with a mobile beacon. In Proceedings First IEEE Conference on Mobile Ad-hoc and Sensor Systems, Fort Lauderdale, FL.

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

    Article  Google Scholar 

  26. Vural, S., & Ekici, E. (2004). Wave addressing for dense sensor networks. In Proceedings IEEE Wokshop on Sensor and Actor Network Protocols and Applications, pp. 56–66.

  27. Xu, Y., Heidemann, J., & Estrin, D. (2001). Geography-informed energy conservation for ad hoc routing. In Proceedings ACM/IEEE MOBICOM, pp. 70–84.

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Authors and Affiliations

  1. Computer Science and Engineering Department, The University of Texas at Arlington, 416 Yates, 300NH, Arlington, TX, 76019, USA

    Rui Huang & Gergely V. Záruba

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  1. Rui Huang
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  2. Gergely V. Záruba
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Correspondence to Gergely V. Záruba.

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Huang, R., Záruba, G.V. Monte Carlo localization of wireless sensor networks with a single mobile beacon. Wireless Netw 15, 978–990 (2009). https://doi.org/10.1007/s11276-008-0096-3

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