An Association Model of Sensor Properties for Event Diffusion Spotting Sensor Networks

  • Xiaoning Cui
  • Qing Li
  • Baohua Zhao
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4976)


Recent years of research on sensor networks have resulted in multi-scale processing techniques for sensor data mining able to reflect the dynamic nature of real-world context. However, few of these techniques provide a systematic view of the relationships between sensor data streams and correlated network behaviors. In this paper, an association model of inherent, data and network properties is presented and analyzed for a suite of event diffusion spotting applications. Based on the associated model, window-based in-network cooperation is conducted for sensitive event diffusion spotting. Experimental results verify the performance of our approach, and confirm the scalability of our association perspective of sensor properties in such event diffusion spotting networks.


Association model Diffusing event Sensor property Correlation In-network cooperation 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Ganesan, D., Estrin, D., Heidemann, J.: Why do we need a new Data Handling architecture for Sensor Networks? In: ACM SIGCOMM Computer Communications Review, pp. 143–148 (2003)Google Scholar
  2. 2.
    Babcok, B., Babu, S., et al.: Models and Issues in Data Stream Systems. In: Proceedings of the 21st ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems, Madison, Wisconsin, USA, pp. 1–16 (2002)Google Scholar
  3. 3.
    Jiang, N., Gruenwald, L.: Research Issues in Data Stream Association Rule Mining. SIGMOD Record 35(1), 14–19 (2006)CrossRefGoogle Scholar
  4. 4.
    Cui, X.N., Zhao, B.H., Li, Q.: Exploiting Data Correlation for Multi-Scale Processing in Sensor Networks. In: 2nd International Conference on Scalable Information Systems, Suzhou, China (2007)Google Scholar
  5. 5.
    Chu, D., Tavakoli, A., Popa, L., Hellerstein, J.: Entirely Declarative Sensor Network System. In: 32nd International Conference on Very Large Data Bases, Seoul, Korea, pp. 1203–1206 (2006)Google Scholar
  6. 6.
    Kotidis, Y., Deligiannakis, A., Stoumpos, V., Vassalos, V., Delis, A.: Robust Management of Outliers in Sensor Network Aggregate Queries. In: 6th International ACM Workshop on Data Engineering for Wireless and Mobile Access, Beijing, China, pp. 17–24 (2007)Google Scholar
  7. 7.
    Jiang, C.Y., Dong, G.Z., Wang, B.: Detection and Tracking of Region-Based Evolving Targets in Sensor Networks. In: 14th International Conference on Computer Communications and Networks, San Diego, California, USA (2005)Google Scholar
  8. 8.
    Subramaniam, S., Palpanas, T., Papadopoulos, D., Kalogeraki, V., Gunopulos, D.: Online Outlier Detection in Sensor Data Using Non-Parametric Models. In: 32nd International Conference on Very Large Data Bases, Seoul, Korea, pp. 187–198 (2006)Google Scholar
  9. 9.
  10. 10.
    Faloutsos, C.: Stream and Sensor data mining. In: 9th International Conference on Extending DataBase Technology, Heraklion-Crete, Greece (2004)Google Scholar
  11. 11.
    Jeffery, S.R., Alonso, G., Franklin, M.: J., Hong, W., Widom, J.: A Pipelined Framework for Online Cleaning of Sensor Data Streams. In: Proceedings of the 22nd International Conference on Data Engineering, Atlanta, GA, USA, IEEE Computer Society Press, Los Alamitos (2006)Google Scholar
  12. 12.
    Quan, Z., Kaiser, W.J., Sayed, A.H.: A Spatial Sampling Scheme Based on Innovations Diffusion in Sensor Networks. In: Proceedings of the 6th International Conference on Information Proceeding in Sensor Networks, Cambridge, Massachusetts, USA, pp. 323–330. ACM Press, New York (2007)CrossRefGoogle Scholar
  13. 13.
    Liu, J.N., Adler, M., Towsley, D., Zhang, C.: On Optimal Communication Cost for Gathering Correlated Data through Wireless Sensor Networks. In: 12th Annual International Conference on Mobile Computing and Networking, Los Angeles, California, USA, pp. 310–321 (2006)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Xiaoning Cui
    • 1
    • 2
    • 3
  • Qing Li
    • 2
    • 3
  • Baohua Zhao
    • 1
    • 2
  1. 1.Department of Computer Science and TechnologyUniversity of Science & Technology of ChinaHefeiChina
  2. 2.Joint Research Lab of ExcellenceCityU-USTC Advanced Research InstituteSuzhouChina
  3. 3.Department of Computer ScienceCity University of Hong KongHong KongChina

Personalised recommendations