Abstract
Storing and disseminating coded information instead of the original data can bring significant performance improvements to sensor network protocols. Such methods reduce the risk of having some data replicated at many nodes, whereas other data is very scarce. This is of particular importance for data persistence in sensor networks. While coding is generally beneficial, coding over all available packets can be detrimental to performance, since coded information might not be decodable after a network failure. In this paper we investigate the suitability of different codeword degree distributions with respect to the dynamics of the underlying wireless network and design a corresponding data management algorithm. We further propose a simple buffer management scheme for continuous data gathering. The performance of the protocols is demonstrated by means of simulation, as well as experiments with an implementation on MICAz motes.
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References
Ahlswede, R., Cai, N., Li, S.-Y., Yeung, R.: Network information flow. IEEE Trans. on Information Theory 46(4), 1204–1216 (2000)
Ho, T., Medard, M., Shi, J., Effros, M., Karger, D.R.: On Randomized Network Coding. In: 41st Annual Allerton Conference on Communication Control and Computing, Monticello, IL, US (October 2003)
Acedanski, S., Deb, S., Medard, M., Koetter, R.: How good is random linear coding based distributed networked storage? In: NetCod, Riva Del Garda, Italy (April 2005)
Deb, S., Medard, M.: Algebraic gossip: A network coding approach to optimal multiple rumor mongering. In: 42nd Annual Allerton Conference on Communication Control and Computing, Monticello, IL (October 2004)
Kamra, A., Misra, V., Feldman, J., Rubenstein, D.: Growth Codes: Maximizing Sensor Network Data Persistence. In: ACM SIGCOMM, Pisa, Italy (September 2006)
Luby, M.: LT Codes. In: 43rd Ann. Symp. on Foundations of Computer Science, Vancouver, Canada (November 2002)
Liu, J., Liu, Z., Towsley, D., Xia, C.H.: Maximizing the data utility of a data archiving and querying system through joint coding and scheduling. In: IPSN 2007, Cambridge, MA, US (April 2007)
Munaretto, D., Widmer, J., Rossi, M., Zorzi, M.: Network coding strategies for data persistence in static and mobile sensor networks. In: WNC3, Limassol, Cyprus (April 2007)
Motwani, R., Raghavan, P.: Randomized Algorithms. Cambridge University Press, New York, NY, US (1995)
Lin, S., Costello, D.: Error Control Coding: Fundamentals and Applications. Prentice-Hall, Englewood Cliffs (1982)
Lin, Y., Liang, B., Li, B.: Data persistence in large-scale sensor networks with decentralized fountain codes. In: INFOCOM 2007, Anchorage, AK, US (May 2007)
Dimakis, A.G., Prabhakaran, V., Ramchandran, K.: Decentralized Erasure Codes for Distributed Networked Storage. IEEE/ACM Trans. on Networking 52(6), 2809–2816 (2006)
Dimakis, A.G., Prabhakaran, V., Ramchandran, K.: Distributed Fountain Codes for Networked Storage. In: IEEE ICASSP, Toulouse, France (May 2006)
Chou, P.A., Wu, T., Jain, K.: Practical network coding. In: 41st Annual Allerton Conference on Communication Control and Computing, Monticello, IL, US (October 2003)
Widmer, J., Fragouli, C., LeBoudec, J.-Y.: Low-complexity energy-efficient broadcasting in wireless ad-hoc networks using network coding. In: NetCod (April 2005)
Fasolo, E., Widmer, J., Rossi, M., Zorzi, M.: A Proactive Network Coding Strategy for Pervasive Wireless Networking. In: IEEE GLOBECOM, Washington, DC, US (November 2007)
CC2420 data sheet. [Online]. Available: http://www.ti.com/
Levis, P., Lee, N.: TOSSIM: A Simulator for TinyOS Networks (June 26, 2003)
Tinyos community forum. [Online]. Available: www.tinyos.net
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Munaretto, D., Widmer, J., Rossi, M., Zorzi, M. (2008). Resilient Coding Algorithms for Sensor Network Data Persistence. In: Verdone, R. (eds) Wireless Sensor Networks. EWSN 2008. Lecture Notes in Computer Science, vol 4913. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77690-1_10
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DOI: https://doi.org/10.1007/978-3-540-77690-1_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-77689-5
Online ISBN: 978-3-540-77690-1
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