Abstract
Wireless Sensor Networks (WSN) monitor the physical world using small wireless devices known as sensor nodes. Location information plays a critical role in many of the applications where WSN are used. A widely used self-locating mechanism consists in equipping a small subset of the nodes with GPS hardware, while the rest of the nodes employ reference estimations (received signal strength, time of arrival, etc.) in order to determine their locations. Finding the location of nodes using node-to-node distances combined with a set of known node locations is referred to as Location Discovery (LD). The main difficulty found in LD is the presence of measurement errors, which results in location errors. We describe in this work an error model for the estimations, propose a two-stage Simulated Annealing to solve the LD problem using this model, and discuss the results obtained. We will put a special stress on the improvements obtained by using our proposed technique.
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References
Nemeroff, J., Garcia, L., Hampel, D., DiPierro, S.: Application of sensor network communications. In: Military Communications Conference (MILCOM) 2001. Communications for Network-Centric Operations: Creating the Information Force, vol. 1, pp. 336–341. IEEE, Los Alamitos (2001)
Lédeczi, Á., Nádas, A., Völgyesi, P., Balogh, G., Kusy, B., Sallai, J., Pap, G., Dóra, S., ároly Molnár, K., Maróti, M., Simon, G.: Countersniper system for urban warfare. ACM Trans. Sen. Netw. 1(2), 153–177 (2005)
Mladineo, N., Knezic, S.: Optimisation of forest fire sensor network using gis technology. In: Proceedings of the 22nd International Conference on Information Technology Interfaces (ITI), pp. 391–396 (2000)
Koushanfar, F., Slijepcevic, S., Potkonjak, M., Sangiovanni-Vincentelli, A.: Location discovery in ad-hoc wireless sensor networks. In: Cheng, X., Huang, X., Du, D.Z. (eds.) Ad Hoc Wireless Networking, pp. 137–173. Kluwer Acad. Publish., Dordrecht (2003)
Karp, B., Kung, H.T.: Gpsr: greedy perimeter stateless routing for wireless networks. In: Proceedings of the 6th annual international conference on Mobile computing and networking (MOBICOM), pp. 243–254. ACM Press, New York (2000)
Moore, D., Leonard, J., Rus, D., Teller, S.: Robust distributed network localization with noisy range measurements. In: Proceedings of the 2nd int. conf. on Embedded networked sensor systems (SenSys), pp. 50–61. ACM, New York (2004)
Merrill, W., Newberg, F., Girod, L., Sohrabi, K.: Battlefield ad-hoc lans: a distributed processing perspective. GOMACTech. (2004)
Girod, L.: Development and characterization of an acoustic rangefinder (2000)
Feng, J., Girod, L., Potkonjak, M.: Location discovery using data-driven statistical error modeling. In: Proceedings of 25th IEEE International Conference on Computer Communications (INFOCOM), pp. 1–14 (2006)
Koushanfar, F., Slijepcevic, S., Wong, J., Potkonjak, M.: Global error-tolerant algorithms for location discovery in ad-hoc wireless networks. In: IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), vol. 4, Proceedings, pp. IV–4186 (2002)
Slijepcevic, S., Megerian, S., Potkonjak, M.: Location errors in wireless embedded sensor networks: sources, models, and effects on applications. SIGMOBILE Mob. Comput. Commun. Rev. 6(3), 67–78 (2002)
Blum, C., Roli, A.: Metaheuristics in combinatorial optimization: Overview and conceptual comparison. ACM Computing Surveys 35(3), 268–308 (2003)
Kirkpatrick, S., Gelatt, C.D., Vecchi, M.P.: Optimization by simulated annealing. Science 4598(220), 671–680 (1983)
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Molina, G., Alba, E. (2009). Location Discovery in Wireless Sensor Networks Using a Two-Stage Simulated Annealing. In: Giacobini, M., et al. Applications of Evolutionary Computing. EvoWorkshops 2009. Lecture Notes in Computer Science, vol 5484. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01129-0_2
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DOI: https://doi.org/10.1007/978-3-642-01129-0_2
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