Abstract
In this paper, we propose a framework for constraint-aware pattern detection over event streams. Given the constraint of the input streams, our proposed framework on the fly checks the query satisfiability / unsatisfiability using a lightweight reasoning mechanism. Based on the constraint specified in the input stream, we are able to adjust the processing strategy dynamically, by producing early feedbacks, releasing unnecessary system resources and terminating corresponding pattern monitor, thus effectively decreasing the resource consumption and expediting the system response on certain situations. Our experimental study illustrates the significant performance improvement achieved by the constraint-aware pattern detection framework with little overhead.
This work has been partially supported by NSF under Grant No. NSF IIS-0414567.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Gartner Inc., http://www.gartner.com
Abadi, D., Carney, D., Cetintemel, U., Cherniack, M., Convey, C., Lee, S., Stonebraker, M., Tatbul, N., Zdonik, S.: Aurora: A new model and architecture for data stream management. VLDB Journal 12(2), 120–139 (2003)
Akdere, M., Cetintemel, U., Tatbul, N.: Plan-based complex event detection across distributed sources. PVLDB 1(1), 66–77 (2008)
Babcock, B., Babu, S., Motwani, R., Widom, J.: Models and issues in data streams. In: PODS, June 2002, pp. 1–16 (2002)
Babu, S., Widom, J.: Continuous queries over data streams. In: ACM SIGMOD (September 2001)
Chandrasekaran, S., Cooper, O., Deshpande, A., Franklin, M., Hellerstein, J., Hong, W., Krishnamurthy, S., Madden, S., Raman, V., Reiss, F., Shah, M.: TelegraphCQ: Continuous dataflow processing for an uncertain world. In: CIDR, pp. 269–280 (2003)
Demers, A.J., Gehrke, J., Panda, B., Riedewald, M., Sharma, V., White, W.M.: Cayuga: A general purpose event monitoring system. In: CIDR, pp. 412–422 (2007)
Ding, L., Chen, S., Rundensteiner, E.A., Tatemura, J., Hsiung, W.-P., Candan, K.S.: Runtime semantic query optimization for event stream processing. In: ICDE, pp. 676–685 (2008)
Etzion, O.: Semantic approach to event processing. In: DEBS, p. 139 (2007)
Harris, C., Gass, S.: Encyclopedia of MS/OR (2000)
Koch, C., Scherzinger, S., Schweikardt, N., Stegmaier, B.: Schema-based scheduling of event processors and buffer minimization for queries on structured data streams. In: VLDB, pp. 228–239 (2004)
Kozen, D.: Automata and computability. W. H. Freeman and Company, New York (2003)
Li, M., Mani, M., Rundensteiner, E.A., Lin, T.: E-tec: A constraint-aware query engine for pattern detection over event streams. In: ICSC, pp. 565–566 (2009)
Liu, M., Li, M., Golovnya, D., Rundensteiner, E.A., Claypool, K.T.: Sequence pattern query processing over out-of-order event streams. In: ICDE, pp. 784–795 (2009)
Schmidt, A., Wass, F.: XMark: a benchmark for XML data management. In: VLDB, pp. 974–985 (2002)
Su, H., Rundensteiner, E.A., Mani, M.: Semantic Query Optimization for XQuery over XML Streams. In: VLDB, pp. 1293–1296 (2005)
Wu, E., Diao, Y., Rizvi, S.: High-performance complex event processing over streams. In: SIGMOD, pp. 407–418 (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Li, M., Mani, M., Rundensteiner, E.A., Lin, T. (2010). Constraint-Aware Complex Event Pattern Detection over Streams. In: Kitagawa, H., Ishikawa, Y., Li, Q., Watanabe, C. (eds) Database Systems for Advanced Applications. DASFAA 2010. Lecture Notes in Computer Science, vol 5982. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12098-5_16
Download citation
DOI: https://doi.org/10.1007/978-3-642-12098-5_16
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-12097-8
Online ISBN: 978-3-642-12098-5
eBook Packages: Computer ScienceComputer Science (R0)