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Efficient Time Aggregation and Querying of Flashed Streams in Constrained Motes

  • Pedro Furtado
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8056)

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.

Keywords

Sensor Node Wireless Sensor Network Sensor Data Query Processing Sink Node 
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.

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References

  1. 1.
    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)Google Scholar
  2. 2.
    Aberer, K., Hauswirth, M., Salehi, A.: Infrastructure for data processing in large-scale interconnected sensor networks. In: Mobile Data Management, Germany (2007)Google Scholar
  3. 3.
    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)Google Scholar
  4. 4.
    Bakshi, A., et al.: The Abstract Task Graph: A Methodology for Architecture-Independent Programming of Networked Sensor Systems. In: Proc. EESR (2005)Google Scholar
  5. 5.
    Bonnet, P., Gehrke, J., Seshadri, P.: Towards sensor database systems. In: Proceedings of the Second International Conference on Mobile Data Management (2001)Google Scholar
  6. 6.
    Boulis, A., et al.: Design and implementation of a framework for efficient and programmable sensor networks. In: Proc. MobiSys (2003)Google Scholar
  7. 7.
    Franklin, M., Jeffery, S., Edakkunni, A., Hong, W., et al.: Design Considerations for High Fan-in Systems: The HiFi Approach. In: CIDR (2005)Google Scholar
  8. 8.
    Gehrke, J., Madden, S.: Query Processing in Sensor Networks. IEEE Pervasive Computing 3(1), 46–55 (2004)CrossRefGoogle Scholar
  9. 9.
    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)Google Scholar
  10. 10.
    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)CrossRefGoogle Scholar
  11. 11.
    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)Google Scholar
  12. 12.
    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)CrossRefGoogle Scholar
  13. 13.
    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)Google Scholar
  14. 14.
    Shen, C.C., et al.: Sensor Information Networking Architecture and Applications. E Personal Communications Magazine 8(4), 52–59 (2001)CrossRefGoogle Scholar
  15. 15.
    Shneidman, J., Pietzuch, P., et al.: Hourglass: An Infrastructure for Connecting Sensor Networks and Applications. Technical Report TR-21-04, Harvard University, EECS (2004) Google Scholar
  16. 16.
    Srisathapornphat, C., et al.: Sensor Information Networking Architecture. In: Proc. Int. Workshops on Parallel Processing (2000)Google Scholar
  17. 17.
    Rosenblum, Ousterhout, J.: The design and implementation of a log structured file system. In: ACM Sympo. on Operating Systems Principles, Pacific Grove, USA (1991)Google Scholar
  18. 18.
    Woo, A., Madden, S., Govindan, R.: Networking support for query processing in sensor networks. Commun. ACM 47(6), 47–52 (2004)CrossRefGoogle Scholar
  19. 19.
    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)Google Scholar
  20. 20.
    Whitehouse, K., Zhao, F., Liu, J.: Semantic Streams: A Framework for Composable Semantic Interpretation of Sensor Data. Wireless Sensor Networks, 5–20 (2006)Google Scholar
  21. 21.
    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)Google Scholar
  22. 22.
    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)CrossRefGoogle Scholar
  23. 23.
    Mottola, L.: Programming Wireless Sensor Networks: From Physical to Logical Neighborhoods. PhD Thesis, Politecnico di Milano, Italy (2008)Google Scholar
  24. 24.
    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)Google Scholar
  25. 25.
    Polastre, J., Szewczyk, R., Culler, D.E.: Telos: enabling ultra-low power wireless research. In: IPSN 2005. IEEE, Los Angeles (2005)Google Scholar
  26. 26.
    Levis, P., Madden, S., et al.: The Emergence of Networking Abstractions and Techniques in TinyOS. In: NSDI 2004, pp. 1–14. USENIX (2004)Google Scholar
  27. 27.
  28. 28.
    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 Google Scholar
  29. 29.
    Pachube [Pachube], https://cosm.com/
  30. 30.
    SensorCloud [SC], http://www.sensorcloud.com/

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Pedro Furtado
    • 1
  1. 1.Univeristy of CoimbraPortugal

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