Abstract
A scalable energy-efficient training protocol is proposed for massively-deployed sensor networks, where sensors are initially anonymous and unaware of their location. The protocol is based on an intuitive coordinate system imposed onto the deployment area which partitions the anonymous sensors into clusters. The protocol is asynchronous, in the sense that the sensors wake up for the first time at random, then alternate between sleep and awake periods both of fixed length, and no explicit synchronization is performed between them and the sink. Theoretical properties are stated under which the training of all the sensors is possible. Moreover, a worst-case analysis as well as an experimental evaluation of the performance is presented, showing that the protocol is lightweight and flexible.
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References
Akyildiz, I.F., Su, W., Sankarasubramanian, Y., Cayirci, E.: Wireless sensor networks: a survey. Computer Networks 38(4), 393–422 (2002)
Bandyopadhyay, S., Coyle, E.: An efficient hierarchical clustering algorithm for wireless sensor networks. In: Proc. IEEE INFOCOM 2003, San Francisco, CA, April 2003 (2003)
Bertossi, A.A., Olariu, S., Pinotti, M.C.: Efficient training of sensor networks. In: Nikoletseas, S.E., Rolim, J.D.P. (eds.) ALGOSENSORS 2006. LNCS, vol. 4240, pp. 1–12. Springer, Heidelberg (2006)
Culler, D., Estrin, D., Srivastava, M.: Overview of sensor networks. IEEE Computer 37(8), 41–49 (2004)
Ghiasi, S., Srivastava, A., Yang, X., Sarrafzadeh, M.: Optimal energy-aware clustering in sensor networks. Sensors 2, 258–269 (2002)
Gorce, J.M., Zhang, R., Parvery, H.: Impact of radio link unreliability on the connectivity of wireless sensor networks. EURASIP Journal on Wireless Communications and Networking (2007)
Griffin, H.: Elementary Theory of Numbers. McGraw Hill, New York (1954)
Langendoen, K., Reijers, N.: Distributed localization algorithm. In: Zurawski, R. (ed.) Embedded Systems Handbook, CRC Press, Boca Raton, FL (2004)
Lee, J.J., Krishnamachari, B., Jay, C.C.: Impact of heterogeneous deployment on lifetime sensing coverage in sensor networks. In: Proc. IEEE SECON (2004)
Nicolescu, D.: Positioning in ad-hoc sensor networks. IEEE Network 18(4), 24–29 (2004)
Olariu, S., Waada, A., Wilson, L., Eltoweissy, M.: Wireless sensor networks leveraging the virtual infrastructure. IEEE Network 18(4), 51–56 (2004)
Waada, A., Olariu, S., Wilson, L., Eltoweissy, M., Jones, K.: Training a wireless sensor network. Mobile Networks and Applications 10(1), 151–168 (2005)
Xu, Q., Ishak, R., Olariu, S., Salleh, S.: On asynchronous training in sensor networks. In: Proc. 3rd Intl. Conf. on Advances in Mobile Multimedia, K.Lumpur (September 2005)
Zhirnov, V.V., Herr, D.J.C.: New frontiers: self-assembly and nano-electronics. IEEE Computer 34(1), 34–43 (2001)
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Barsi, F., Bertossi, A.A., Sorbelli, F.B., Ciotti, R., Olariu, S., Pinotti, C.M. (2008). Asynchronous Training in Wireless Sensor Networks. In: Kutyłowski, M., Cichoń, J., Kubiak, P. (eds) Algorithmic Aspects of Wireless Sensor Networks. ALGOSENSORS 2007. Lecture Notes in Computer Science, vol 4837. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77871-4_6
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DOI: https://doi.org/10.1007/978-3-540-77871-4_6
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