Energy-Efficient Multi-query Optimization over Large-Scale Sensor Networks (original) (raw)

Abstract

Currently much research work has been done to attempt to efficiently conserve the energy consumption for sensor networks, recently a database approach to programming sensor networks has gained much attention from the sensor network research area. In this paper we developed an optimized multi-query processing paradigm for aggregate queries, we proposed an equivalence class based merging algorithm for in-network merging of partial aggregate values of multi-queries, and an adaptive fusion degree based routing scheme as a cross-layer designing technique. Our optimized multi-query processing paradigm efficiently takes advantage of the work sharing mechanism by sharing common aggregate values among multiple queries to fully reduce the communication cost for sensor networks, thus extending the life time of sensor networks. The experimental evaluation shows that our optimization paradigm can efficiently result in dramatic energy savings, compared to previous work.

This work is partially supported by the National Basic Research Program of China (973) under Grant No.2002CB312002, the National Natural Science Foundation of China under Grant No.60573132.

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References

  1. Trigoni, N., Yao, Y., Demers, A., Gehrke, J., Rajaraman, R.: Multi-query Optimization for Sensor Networks. In: Prasanna, V.K., Iyengar, S.S., Spirakis, P.G., Welsh, M. (eds.) DCOSS 2005. LNCS, vol. 3560, pp. 307–321. Springer, Heidelberg (2005)
    Chapter Google Scholar
  2. Emekci, F., Yu, H., Agrawal, D.: Amr El Abbadi Energy-Conscious Data Aggregation Over Large-Scale Sensor Networks
    Google Scholar
  3. Madden, S., Franklin, M.J., Hellerstein, J.M., Hong, W.: TAG: A Tiny AGgregation Service for Ad-Hoc Sensor Networks. In: OSDI (2002)
    Google Scholar
  4. Intanagonwiwat, C., Govindan, R., Estrin, D.: Directed diffusion: A scalable and robust communication paradigm for sensor networks. In: MobiCOM, Boston, MA (August 2000)
    Google Scholar
  5. Madden, S., Franklin, M.J.: Fjording the stream: An architechture for queries over streaming sensor data. In: ICDE (2002)
    Google Scholar
  6. Yao, Y., Gehrke, J.: The cougar approach to in-network query processing in sensor networks. In: SIGMOD Record (September 2002)
    Google Scholar
  7. Yao, Y., Gehrke, J.: Query processing in sensor networks. In: Proceedings of the First Biennial Conference on Innovative Data Systems Research (CIDR) (2003)
    Google Scholar
  8. Madden, S., Franklin, M.J., Hellerstein, J.M., Hong, W.: TinyDB: an acquisitional query processing system for sensor networks. ACM Trans. Database Syst. 30(1), 122–173 (2005)
    Article Google Scholar
  9. Trigoni, N., Yao, Y., Demers, A.J., Gehrke, J., Rajaraman, R.: Hybrid Push-Pull Query Processing for Sensor Networks. GI Jahrestagung (2), 370–374 (2004)
    Google Scholar
  10. Madden, S.: The Design and Evaluation of a Query Processing Architecture for Sensor Networks. Ph. D Thesis, UC Berkeley, Fall (2003)
    Google Scholar
  11. Krishnamachari, B., Estrin, D., Wicker, S.B.: The Impact of Data Aggregation in Wireless Sensor Networks. In: ICDCS Workshops 2002, pp. 575–578 (2002)
    Google Scholar
  12. Demers, A.J., Gehrke, J., Rajaraman, R., Trigoni, A., Yao, Y.: The Cougar Project: a work-in-progress report. SIGMOD Record 32(4), 53–59 (2003)
    Article Google Scholar
  13. Gehrke, J., Madden, S.: Query Processing in Sensor Networks Sensor and Actuator Networks
    Google Scholar

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Authors and Affiliations

  1. State Key Laboratory of Novel Software Technology, NJU-POLYU Cooperative Laboratory for Wireless Sensor Network, Nanjing University, Nanjing, China
    Lei Xie, Lijun Chen, Sanglu Lu, Li Xie & Daoxu Chen

Authors

  1. Lei Xie
  2. Lijun Chen
  3. Sanglu Lu
  4. Li Xie
  5. Daoxu Chen

Editor information

Editors and Affiliations

  1. Department of Computer Science, The George Washington University, 801 22nd Street NW, Suite 704., 20052, Washington DC, USA
    Xiuzhen Cheng
  2. School of Information Science and Technology, Sun Yat-sen University, 510275, Guangzhou, China
    Wei Li
  3. Computer Science Department, University of Pittsburgh, PA 15260, Pittsburgh, USA
    Taieb Znati

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© 2006 Springer-Verlag Berlin Heidelberg

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Xie, L., Chen, L., Lu, S., Xie, L., Chen, D. (2006). Energy-Efficient Multi-query Optimization over Large-Scale Sensor Networks. In: Cheng, X., Li, W., Znati, T. (eds) Wireless Algorithms, Systems, and Applications. WASA 2006. Lecture Notes in Computer Science, vol 4138. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11814856\_14

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