Advertisement

Extensions to Stream Processing Architecture for Supporting Event Processing

  • Vihang Garg
  • Raman Adaikkalavan
  • Sharma Chakravarthy
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4080)

Abstract

Both event and stream data processing models have been researched independently and are utilized in diverse application domains. Although they complement each other in terms of their functionality, there is a critical need for their synergistic integration to serve newer class of pervasive and sensor-based monitoring applications. For instance, many advanced applications generate interesting simple events as a result of stream processing that need to be further composed and detected for triggering appropriate actions. In this paper, we present EStream, an approach for integrating event and stream processing for monitoring changes on stream computations and for expressing and processing complex events on continuous queries (CQs). We introduce masks for reducing uninteresting events and for detecting events correctly and efficiently. We discuss stream modifiers, a special class of stream operators for computing changes over stream data. We also briefly discuss architecture and functional modules of EStream.

Keywords

Event Processing Stream Processing Query Plan Continuous Query Event Object 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Madden, S., Franklin, M.J.: Fjording the Stream: An Architecture for Queries over Streaming Sensor Data. In: Proc. of ICDE (2002)Google Scholar
  2. 2.
    Chen, J., et al.: NiagaraCQ: A Scalable Continuous Query System for Internet Databases. In: Proc. of SIGMOD (2000)Google Scholar
  3. 3.
    Babcok, B., et al.: Operator scheduling in data stream systems. The VLDB J. 13, 333–353 (2004)CrossRefGoogle Scholar
  4. 4.
    Jiang, Q., Chakravarthy, S.: Scheduling Strategies for Processing Continuous Queries over Streams. In: Williams, H., MacKinnon, L.M. (eds.) BNCOD 2004. LNCS, vol. 3112, pp. 16–30. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  5. 5.
    Babcock, B., Datar, M., Motwani, R.: Load Shedding for Aggregation Queries over Data Streams. In: Proc. of ICDE (March 2004)Google Scholar
  6. 6.
    Tatbul, N., et al.: Load Shedding in a Data Stream Manager. In: Proc. of VLDB (September 2003)Google Scholar
  7. 7.
    Buchmann, A.P., et al.: Rules in an Open System: The REACH Rule System. Rules in Database Systems (1993)Google Scholar
  8. 8.
    Gatziu, S., Dittrich, K.R.: Events in an Object-Oriented Database System. In: Proceedings of Rules in Database Systems (September 1993)Google Scholar
  9. 9.
    Chakravarthy, S., Mishra, D.: Snoop: An Expressive Event Specification Language for Active Databases. Data and Knowledge Engineering 14(10), 1–26 (1994)CrossRefGoogle Scholar
  10. 10.
    Chakravarthy, S., et al.: Design of Sentinel: An Object-Oriented DBMS with Event-Based Rules. Information and Software Technology 36(9), 559–568 (1994)CrossRefGoogle Scholar
  11. 11.
    Adaikkalavan, R., Chakravarthy, S.: SnoopIB: Interval-Based Event Specification and Detection for Active Databases (in press) (2005), Available: http://dx.doi.org/10.1016/j.datak.2005.07.009
  12. 12.
    Jiang, Q., Chakravarthy, S.: Data Stream Management System for MavHome. In: Proc. of ACM SAC (March 2004)Google Scholar
  13. 13.
    Gilani, A., Sonune, S., Kendai, B., Chakravarthy, S.: The Anatomy of a Stream Processing System. In: Bell, D.A., Hong, J. (eds.) BNCOD 2006. LNCS, vol. 4042, pp. 232–239. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  14. 14.
    Chakravarthy, S., Pajjuri, V.: Scheduling Strategies and Their Evaluation in a Data Stream Management System. In: Bell, D.A., Hong, J. (eds.) BNCOD 2006. LNCS, vol. 4042, pp. 220–231. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  15. 15.
    Garg, V.: Estream: An integration of event and stream processing. Master’s thesis, The Univ. of Texas at Arlington (2005), [Online] Available: http://itlab.uta.edu/ITLABWEB/Students/sharma/theses/Gar05MS.pdf
  16. 16.
    Jiang, Q., Adaikkalavan, R., Chakravarthy, S.: Towards an Integrated Model for Event and Stream Processing. TR CSE-2004-10, CSE Dept., Univ. of Texas at Arlington (2004)Google Scholar
  17. 17.
    Arasu, A., et al.: Linear Road: A Stream Data Management Benchmark. In: Proc. of VLDB (September 2004)Google Scholar
  18. 18.
    Motwani, R., et al.: Query Processing, Resource Management, and Approximation in a Data Stream Management System. In: Proc. of CIDR (January 2003)Google Scholar
  19. 19.
    Rizvi, S., et al.: Events on the edge (demo). In: Proc. of SIGMOD (2005)Google Scholar
  20. 20.
    Madden, S.R., et al.: The Design of an Acquisitional Query Processor for Sensor Networks. In: Proc. of SIGMOD (2003)Google Scholar
  21. 21.
    Madden, S.R., et al.: TAG: a Tiny AGgregation Service for Ad-Hoc Sensor Networks. In: Proc. of OSDI (December 2002)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Vihang Garg
    • 1
  • Raman Adaikkalavan
    • 1
  • Sharma Chakravarthy
    • 1
  1. 1.IT Laboratory & Department of Computer Science and EngineeringThe University of Texas at ArlingtonArlingtonUSA

Personalised recommendations