Runtime semantic query optimization for event stream processing

Luping Ding, Songting Chen, Elke A. Rundensteiner, Junichi Tatemura, Wang Pin Hsiung, Kasim Candan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

40 Citations (Scopus)

Abstract

Detecting complex patterns in event streams, i.e., complex event processing (CEP), has become increasingly important for modern enterprises to react quickly to critical situations. In many practical cases business events are generated based on pre-defined business logics. Hence constraints, such as occurrence and order constraints, often hold among events. Reasoning using these known constraints enables us to predict the non-occurrences of certain future events, thereby helping us to identify and then terminate the long running query processes that are guaranteed to not lead to successful matches. In this work, we focus on exploiting event constraints to optimize CEP over large volumes of business transaction streams. Since the optimization opportunities arise at runtime, we develop a runtime query unsatisfiability (RunSAT) checking technique that detects optimal points for terminating query evaluation. To assure efficiency of RunSAT checking, we propose mechanisms to precompute the query failure conditions to be checked at runtime. This guarantees a constant-time RunSAT reasoning cost, making our technique highly scalable. We realize our optimal query termination strategies by augmenting the query with Event-Condition-Action rules encoding the pre-computed failure conditions. This results in an event processing solution compatible with state-of-the-art CEP architectures. Extensive experimental results demonstrate that significant performance gains are achieved, while the optimization overhead is small.

Original languageEnglish (US)
Title of host publicationProceedings - International Conference on Data Engineering
Pages676-685
Number of pages10
DOIs
StatePublished - 2008
Externally publishedYes
Event2008 IEEE 24th International Conference on Data Engineering, ICDE'08 - Cancun, Mexico
Duration: Apr 7 2008Apr 12 2008

Other

Other2008 IEEE 24th International Conference on Data Engineering, ICDE'08
CountryMexico
CityCancun
Period4/7/084/12/08

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Semantics
Processing
Industry
Costs

ASJC Scopus subject areas

  • Information Systems
  • Signal Processing
  • Software

Cite this

Ding, L., Chen, S., Rundensteiner, E. A., Tatemura, J., Hsiung, W. P., & Candan, K. (2008). Runtime semantic query optimization for event stream processing. In Proceedings - International Conference on Data Engineering (pp. 676-685). [4497476] https://doi.org/10.1109/ICDE.2008.4497476

Runtime semantic query optimization for event stream processing. / Ding, Luping; Chen, Songting; Rundensteiner, Elke A.; Tatemura, Junichi; Hsiung, Wang Pin; Candan, Kasim.

Proceedings - International Conference on Data Engineering. 2008. p. 676-685 4497476.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Ding, L, Chen, S, Rundensteiner, EA, Tatemura, J, Hsiung, WP & Candan, K 2008, Runtime semantic query optimization for event stream processing. in Proceedings - International Conference on Data Engineering., 4497476, pp. 676-685, 2008 IEEE 24th International Conference on Data Engineering, ICDE'08, Cancun, Mexico, 4/7/08. https://doi.org/10.1109/ICDE.2008.4497476
Ding L, Chen S, Rundensteiner EA, Tatemura J, Hsiung WP, Candan K. Runtime semantic query optimization for event stream processing. In Proceedings - International Conference on Data Engineering. 2008. p. 676-685. 4497476 https://doi.org/10.1109/ICDE.2008.4497476
Ding, Luping ; Chen, Songting ; Rundensteiner, Elke A. ; Tatemura, Junichi ; Hsiung, Wang Pin ; Candan, Kasim. / Runtime semantic query optimization for event stream processing. Proceedings - International Conference on Data Engineering. 2008. pp. 676-685
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