Abstract
We propose and evaluate efficient, low-memory and low-consumption organization and query processing algorithms for a tiny Stream Management Engine (SME). The target sensor devices have low memory and computation capabilities, and high wireless data transmission costs. The SME represents data as streams, we discuss the approach and study how to optimize group-by aggregation over time-ordered data in that context, and to provide simple all-purpose group-by and join algorithms. We used an experimental testbed to evaluate the findings and prove the advantage of the alternatives and studies that we made.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Diao, Y., Ganesan, D., Mathur, G., Shenoy, P.J.: Rethinking Data Management for Storage-centric Sensor Networks. In: CIDR, Asilomar, USA, pp. 22–31 (January 2007)
Aberer, K., Hauswirth, M., Salehi, A.: Infrastructure for data processing in large-scale interconnected sensor networks. In: Mobile Data Management, Germany (2007)
Agrawal, D., Ganesan, D., et al.: Lazy- adaptive tree: An optimized index structure for flash devices. In: Proceedings of IC Very Large Data Bases (VLDB), Lyon, France (August 2009)
Bakshi, A., et al.: The Abstract Task Graph: A Methodology for Architecture-Independent Programming of Networked Sensor Systems. In: Proc. EESR (2005)
Bonnet, P., Gehrke, J., Seshadri, P.: Towards sensor database systems. In: Proceedings of the Second International Conference on Mobile Data Management (2001)
Boulis, A., et al.: Design and implementation of a framework for efficient and programmable sensor networks. In: Proc. MobiSys (2003)
Franklin, M., Jeffery, S., Edakkunni, A., Hong, W., et al.: Design Considerations for High Fan-in Systems: The HiFi Approach. In: CIDR (2005)
Gehrke, J., Madden, S.: Query Processing in Sensor Networks. IEEE Pervasive Computing 3(1), 46–55 (2004)
Gibbons, P.B., Karp, B., Ke, Y., Nath, S., Seshan, S.: IrisNet: An Architecture for a World- Wide Sensor Web. IEEE Pervasive Computing 2(4) (2003)
Gummadi, R., Gnawali, O., Govindan, R.: Macro-programming wireless sensor networks using kairos. In: Prasanna, V.K., Iyengar, S.S., Spirakis, P.G., Welsh, M. (eds.) DCOSS 2005. LNCS, vol. 3560, pp. 126–140. Springer, Heidelberg (2005)
Li, S., et al.: Event Detection Services Using Data Service Middleware in Distributed Sensor Networks. In: Proc. Int. Workshop on Information Processing in Sensor Networks (2003)
Madden, S., Franklin, M., et al.: TinyDB: an acquisitional query processing system for sensor networks. ACM Trans. on Database Systems 30(1), 122–173 (2005)
Nath, S., Kansal, A.: FlashDB: Dynamic self-tuning database for NAND flash. In: International Conf. on Information Processing in Sensor Networks Cambridge, USA (April 2007)
Shen, C.C., et al.: Sensor Information Networking Architecture and Applications. E Personal Communications Magazine 8(4), 52–59 (2001)
Shneidman, J., Pietzuch, P., et al.: Hourglass: An Infrastructure for Connecting Sensor Networks and Applications. Technical Report TR-21-04, Harvard University, EECS (2004)
Srisathapornphat, C., et al.: Sensor Information Networking Architecture. In: Proc. Int. Workshops on Parallel Processing (2000)
Rosenblum, Ousterhout, J.: The design and implementation of a log structured file system. In: ACM Sympo. on Operating Systems Principles, Pacific Grove, USA (1991)
Woo, A., Madden, S., Govindan, R.: Networking support for query processing in sensor networks. Commun. ACM 47(6), 47–52 (2004)
Zeinalipour-Yazti, Lin, S., et al.: MicroHash: An efficient index structure for flash-based sensor devices. In: USENIX FAST 2005, San Francisco, CA, USA (2005)
Whitehouse, K., Zhao, F., Liu, J.: Semantic Streams: A Framework for Composable Semantic Interpretation of Sensor Data. Wireless Sensor Networks, 5–20 (2006)
Yoneki, E., Bacon, J.: A survey of Wireless Sensor Network technologies: research trends and middleware’s role. Tech. R. of Univ of Cambridge, UCAM-CL-TR-646 (2005)
Wang, M.M., Cao, J.N., Li, J., et al.: Middleware for wireless sensor networks: A survey. Journal of Computer Science and Technology 23(3), 305–326 (2008)
Mottola, L.: Programming Wireless Sensor Networks: From Physical to Logical Neighborhoods. PhD Thesis, Politecnico di Milano, Italy (2008)
Schreiber, F.A., et al.: PERLA: a Data Language for Pervasive Systems. In: Sixth International Conf. on Pervasive Computing and Communications, Hong Kong, pp. 282–287 (2008)
Polastre, J., Szewczyk, R., Culler, D.E.: Telos: enabling ultra-low power wireless research. In: IPSN 2005. IEEE, Los Angeles (2005)
Levis, P., Madden, S., et al.: The Emergence of Networking Abstractions and Techniques in TinyOS. In: NSDI 2004, pp. 1–14. USENIX (2004)
Dunkels, A., Grönvall, B., Voigt, T.: Contiki - A Lightweight and Flexible Operating System for Tiny Networked Sensors. In: LCN 2004 (2004) ISBN 0-7695-2260-2
Pachube [Pachube], https://cosm.com/
SensorCloud [SC], http://www.sensorcloud.com/
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Furtado, P. (2013). Efficient Time Aggregation and Querying of Flashed Streams in Constrained Motes. In: Decker, H., Lhotská, L., Link, S., Basl, J., Tjoa, A.M. (eds) Database and Expert Systems Applications. DEXA 2013. Lecture Notes in Computer Science, vol 8056. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40173-2_14
Download citation
DOI: https://doi.org/10.1007/978-3-642-40173-2_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-40172-5
Online ISBN: 978-3-642-40173-2
eBook Packages: Computer ScienceComputer Science (R0)