Abstract
A current challenge in wireless sensor networks is the positioning of sensor nodes for indoor environments without dedicated hardware. Especially in this domain, many applications rely on spatial information to relate collected data to the location of its origin. First of all, an estimation of the distance between two nodes is necessary to determine their positions. So far, the majority of approaches have explored physical properties of signals such as the strength of a received signal or its arrival time. However, this has been problematic since either the complexity on the software or on the hardware side is not adequate for embedded systems, or the approaches lack the required accuracy. In this paper we present the DIN algorithm (Distance by Intersection of Neighborhoods) to determine the distance between two nodes in an Ad-hoc manner, relying solely on the investigation of local node densities. To evaluate the accuracy of this algorithm, we conducted extensive simulations and experimented with different testbed setups using real sensor nodes. We were able to assure competitive values for the measured error.
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References
Akyildiz, I., Su, W., Sankarasubramaniam, Y., Cayirci, E.: A survey on sensor networks. Journal Communications Magazine, 102–114. IEEE (2002)
Simon, G., Maróti, M., Lédeczi, Á., Balogh, G., Kusy, B., Nádas, A., Pap, G., Sallai, J., Frampton, K.: Sensor network-based countersniper system. In: SenSys 2004: Proceedings of the 2nd international conference on Embedded networked sensor systems, Baltimore, MD, USA, pp. 1–12. ACM Press, New York (2004)
Priyantha, N.B.: The Cricket Indoor Location System. PhD thesis, Massachusetts Institute of Technology (2005)
Broxton, M., Lifton, J., Paradiso, J.: Localizing a sensor network via collaborative processing of global stimuli. In: Proceedings of the Second European Workshop on Wireless Sensor Networks, pp. 321–332. IEEE, Los Alamitos (2005)
Maróti, M., Völgyesi, P., Dóra, S., Kusý, B., Nádas, A., Lédeczi, Á., Balogh, G., Molnár, K.: Radio interferometric geolocation. In: SenSys 2005: Proceedings of the 3rd International Conference on Embedded Networked Sensor Systems, pp. 1–12. ACM Press, New York (2005)
Lenz, D.: Homepage of the ekahau project (2007), http://www.ekahau.com/
Microsoft-Research: Homepage of the easyliving project (2007), http://research.microsoft.com/easyliving
FU-Berlin: Homepage of the scatterweb project (2007), http://www.scatterweb.mi.fu-berlin.de
López-Villafuerte, F., Terfloth, K., Schiller, J.: Using network density as a new parameter to estimate distance. In: The Seventh International Conference on Networking, ICN 2008, Cancun, Mexico, p. 6. IEEE Press, Los Alamitos (2008)
He, T., Huang, C., Blum, B., Stankovic, J., Abdelzaher, T.: Range-free localization schemes in large scale sensor networks. In: MobiCom 2003: Proceedings of the 9th annual international conference on Mobile computing and networking, pp. 81–95. ACM Press, New York (2003)
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López Villafuerte, F., Schiller, J. (2008). DIN: An Ad-Hoc Algorithm to Estimate Distances in Wireless Sensor Networks. In: Coudert, D., Simplot-Ryl, D., Stojmenovic, I. (eds) Ad-hoc, Mobile and Wireless Networks. ADHOC-NOW 2008. Lecture Notes in Computer Science, vol 5198. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85209-4_13
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DOI: https://doi.org/10.1007/978-3-540-85209-4_13
Publisher Name: Springer, Berlin, Heidelberg
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