Abstract
Wireless sensor networks are often densely deployed for environmental monitoring applications. Collecting raw data from these networks can lead to excessive energy consumption. Thus using the spatial and temporal correlations that exist between adjacent nodes we appoint a few as representative nodes that perform in-network aggregation. This reduces the total number of transmissions. Our distributed scheduling algorithm autonomously assigns a particular node to perform aggregation and reassigns schedules when network topology changes. These topology changes are detected using cross-layer information from the underlying MAC layer. We also present theoretical performance estimates and upper bounds of our algorithm and evaluate it by implementing the algorithm on actual sensor nodes, demonstrating an energy-saving of up to 80% compared to raw data collection.
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References
Ambient systems (2006), http://www.ambient-systems.net/ambient/index.htm
Chatterjea, S., Nieberg, T., Meratnia, N., Havinga, P.J.M.: A distributed and self-organizing scheduling algorithm for energy-efficient data aggregation in wireless sensor networks. Technical Report TR-CTIT-07-10, Enschede (February 2007)
Chu, D., Deshpande, A., Hellerstein, J.M., Hong, W.: Approximate data collection in sensor networks using probabilistic models. In: ICDE, p. 48 (2006)
Crescenzi, P., Kann, V.: A compendium of np optimization problems: Maximum independent set (2005), http://www.nada.kth.se/ viggo/wwwcompendium/node34.html
Dolev, S.: Self-Stabilization. MIT Press, Cambridge (2000)
Heinzelman, W.B., Chandrakasan, A.P., Balakrishnan, H.: An application-specific protocol architecture for wireless microsensor networks. Wireless Communications, IEEE Transactions on 1(4), 660–670 (2002)
Herman, T.: Models of self-stabilization and sensor networks. In: IWDC 2003. LNCS, vol. 2918, pp. 205–214. Springer, Heidelberg (2003)
Hoesel, L.v. Havinga, P.: A lightweight medium access protocol (lmac) for wireless sensor networks: Reducing preamble transmissions and transceiver state switches. In: INSS, Tokyo, Japan (June 2004)
Liu, C., Wu, K., Pei, J.: An energy efficient data collection framework for wireless sensor networks by exploiting spatiotemporal correlation. IEEE Transactions on Parallel and Distributed Systems (To appear)
Tulone, D., Madden, S.: An energy-efficient querying framework in sensor networks for detecting node similarities. In: MSWiM, pp. 191–300 (2006)
Tulone, D., Madden, S.: Paq: Time series forecasting for approximate query answering in sensor networks. In: Römer, K., Karl, H., Mattern, F. (eds.) EWSN 2006. LNCS, vol. 3868, Springer, Heidelberg (2006)
van Hoesel, L.F.W., Havinga, P.J.M.: Design aspects of an energy-efficient, lightweight medium access control protocol for wireless sensor networks. Technical Report TR-CTIT-06-47, Enschede (July 2006)
Vuran, M.C., Akan, B., Akyildiz, I.F.: Spatio-temporal correlation: theory and applications for wireless sensor networks. Comput. Networks 45(3), 245–259 (2004)
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Chatterjea, S., Nieberg, T., Zhang, Y., Havinga, P. (2007). Energy-Efficient Data Acquisition Using a Distributed and Self-organizing Scheduling Algorithm for Wireless Sensor Networks. In: Aspnes, J., Scheideler, C., Arora, A., Madden, S. (eds) Distributed Computing in Sensor Systems. DCOSS 2007. Lecture Notes in Computer Science, vol 4549. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73090-3_25
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DOI: https://doi.org/10.1007/978-3-540-73090-3_25
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-73089-7
Online ISBN: 978-3-540-73090-3
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