Data Stream Sharing | SpringerLink
Skip to main content
Springer Nature Link
Log in

Data Stream Sharing

  • Conference paper
Current Trends in Database Technology – EDBT 2006 (EDBT 2006)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 4254))

Included in the following conference series:

Abstract

Recent research efforts in the fields of data stream processing and data stream management systems (DSMSs) show the increasing importance of processing data streams, e. g., in the e-science domain. Together with the advent of peer-to-peer (P2P) networks and grid computing, this leads to the necessity of developing new techniques for distributing and processing continuous queries over data streams in such networks. In this paper, we present a novel approach for optimizing the integration, distribution, and execution of newly registered continuous queries over data streams in grid-based P2P networks. We introduce Windowed XQuery (WXQuery), our XQuery-based subscription language for continuous queries over XML data streams supporting window-based operators. Concentrating on filtering and window-based aggregation, we present our stream sharing algorithms as well as experimental evaluation results from the astrophysics application domain to assess our approach.

This research is supported by the German Federal Ministry of Education and Research within the D-Grid initiative under contract 01AK804F and by Microsoft Research Cambridge under contract 2005-041.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Stegmaier, B., Kuntschke, R., Kemper, A.: StreamGlobe: Adaptive Query Processing and Optimization in Streaming P2P Environments. In: Proc. of the Intl. Workshop on Data Management for Sensor Networks, Toronto, Canada, pp. 88–97 (2004)

    Google Scholar 

  2. Kuntschke, R., Stegmaier, B., Kemper, A., Reiser, A.: StreamGlobe: Processing and Sharing Data Streams in Grid-Based P2P Infrastructures. In: Proc. of the Intl. Conf. on Very Large Data Bases, Trondheim, Norway, pp. 1259–1262 (2005)

    Google Scholar 

  3. Yang, B., Garcia-Molina, H.: Designing a Super-Peer Network. In: Proc. of the IEEE Intl. Conf. on Data Engineering, Bangalore, India, pp. 49–60 (2003)

    Google Scholar 

  4. W3C: XQuery 1.0: An XML Query Language (W3C Candidate Recommendation, November 3, 2005) (2005), http://www.w3.org/TR/xquery/

  5. Rosenkrantz, D.J., Hunt, H.B.: Processing Conjunctive Predicates and Queries. In: Proc. of the Intl. Conf. on Very Large Data Bases, Montreal, Canada, pp. 64–72 (1980)

    Google Scholar 

  6. Arasu, A., Widom, J.: Resource Sharing in Continuous Sliding-Window Aggregates. In: [18], pp. 336–347

    Google Scholar 

  7. Abadi, D.J., Ahmad, Y., Balazinska, M., Çetintemel, U., Cherniack, M., Hwang, J.H., Lindner, W., Maskey, A.S., Rasin, A., Ryvkina, E., Tatbul, N., Xing, Y., Zdonik, S.: The Design of the Borealis Stream Processing Engine. In: Proc. of the Conf. on Innovative Data Systems Research, Asilomar, CA, USA, pp. 277–289 (2005)

    Google Scholar 

  8. Arasu, A., Babcock, B., Babu, S., Datar, M., Ito, K., Motwani, R., Nishizawa, I., Srivastava, U., Thomas, D., Varma, R., Widom, J.: STREAM: The Stanford Stream Data Manager. IEEE Data Engineering Bulletin 26(1), 19–26 (2003)

    Google Scholar 

  9. Chandrasekaran, S., Cooper, O., Deshpande, A., Franklin, M.J., Hellerstein, J.M., Hong, W., Krishnamurthy, S., Madden, S., Raman, V., Reiss, F., Shah, M.A.: TelegraphCQ: Continuous Dataflow Processing for an Uncertain World. In: [19]

    Google Scholar 

  10. Chen, J., DeWitt, D.J., Tian, F., Wang, Y.: NiagaraCQ: A Scalable Continuous Query System for Internet Databases. In: Proc. of the ACM SIGMOD Intl. Conf. on Management of Data, Dallas, TX, USA, pp. 379–390 (2000)

    Google Scholar 

  11. Cherniack, M., Balakrishnan, H., Balazinska, M., Carney, D., Çetintemel, U., Xing, Y., Zdonik, S.B.: Scalable Distributed Stream Processing. In: [19]

    Google Scholar 

  12. Yao, Y., Gehrke, J.: The Cougar Approach to In-Network Query Processing in Sensor Networks. ACM SIGMOD Record 31(3), 9–18 (2002)

    Article  Google Scholar 

  13. Sellis, T.K.: Multiple-Query Optimization. ACM Trans. on Database Systems 13(1), 23–52 (1988)

    Article  Google Scholar 

  14. Madden, S., Shah, M.A., Hellerstein, J.M., Raman, V.: Continuously Adaptive Continuous Queries over Streams. In: Proc. of the ACM SIGMOD Intl. Conf. on Management of Data, Madison, WI, USA, pp. 49–60 (2002)

    Google Scholar 

  15. Krishnamurthy, S., Franklin, M.J., Hellerstein, J.M., Jacobson, G.: The Case for Precision Sharing. In: [18], pp. 972–986

    Google Scholar 

  16. Dong, X., Halevy, A.Y., Tatarinov, I.: Containment of Nested XML Queries. In: [18], pp. 132–143

    Google Scholar 

  17. Kuntschke, R., Stegmaier, B., Kemper, A.: Data Stream Sharing. Technical Report TUM-I0504, Technische Universität München (2005)

    Google Scholar 

  18. Proc. of the Intl. Conf. on Very Large Data Bases, Toronto, Canada (2004)

    Google Scholar 

  19. Proc. of the Conf. on Innovative Data Systems Research, Asilomar, CA, USA (2003)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institut für Informatik, Technische Universität München, Munich, Germany

    Richard Kuntschke & Alfons Kemper

Authors
  1. Richard Kuntschke
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Alfons Kemper
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Technische Universität München, Germany

    Torsten Grust

  2. International University in Germany, Germany

    Hagen Höpfner

  3. University of the Basque Country,  

    Arantza Illarramendi

  4. University of Bayreuth, Bayreuth, Germany

    Stefan Jablonski

  5. Università di Milano, Italy

    Marco Mesiti

  6. University of Erlangen-Nurmberg, Germany

    Sascha Müller

  7. Institut für Informatik, Ludwig-Maximilians-Universität, Oettingenstr. 67, 80538, München, Germany

    Paula-Lavinia Patranjan

  8. Dept. of Computer Science and Automation, TU Ilmenau

    Kai-Uwe Sattler

  9. Faculty of Computer Science, Otto-von-Guericke-University Magdeburg, Germany

    Myra Spiliopoulou

  10. Université de Mons-Hainaut, Mons, Belgium

    Jef Wijsen

Rights and permissions

Reprints and permissions

Copyright information

© 2006 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Kuntschke, R., Kemper, A. (2006). Data Stream Sharing. In: Grust, T., et al. Current Trends in Database Technology – EDBT 2006. EDBT 2006. Lecture Notes in Computer Science, vol 4254. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11896548_58

Download citation

  • DOI: https://doi.org/10.1007/11896548_58

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-46788-5

  • Online ISBN: 978-3-540-46790-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation