Ming Li
Murali Mani
ABSTRACT
In this work, we study the event pattern matching mechanism over streams with interval-based temporal semantics. An expressive language to represent the required temporal patterns among streaming interval events is introduced and the corresponding temporal operator ISEQ is designed. For further improving the interval event processing performance, a punctuation-aware stream processing strategy is provided. Experimental studies illustrate that the proposed techniques bring significant performance improvement in both memory and CPU usage with little overhead.
- D. Abadi, D. Carney, U. Cetintemel, M. Cherniack, C. Convey, S. Lee, M. Stonebraker, N. Tatbul, and S. Zdonik. Aurora: A new model and architecture for data stream management. VLDB Journal, 12(2):120--139, August 2003. Google Scholar
Digital Library
- J. Agrawal, Y. Diao, D. Gyllstrom, and N. Immerman. Efficient pattern matching over event streams. In SIGMOD, pages 147--160, 2008. Google ScholarDigital Library
- M. Akdere, U. Cetintemel, and N. Tatbul. Plan-based complex event detection across distributed sources. PVLDB, 1(1):66--77, 2008. Google ScholarDigital Library
- J. F. Allen. Maintaining knowledge about temporal intervals. Commun. ACM, 26(11):832--843, 1983. Google ScholarDigital Library
- S. Babu and J. Widom. Continuous queries over data streams. SIGMOD Record, 30(3):109--120, 2001. Google ScholarDigital Library
- G. Cugola and A. Margara. Tesla: a formally defined event specification language. In DEBS, pages 50--61, 2010. Google ScholarDigital Library
- A. J. Demers, J. Gehrke, B. Panda, M. Riedewald, V. Sharma, and W. M. White. Cayuga: A general purpose event monitoring system. In CIDR, pages 412--422, 2007.Google Scholar
- L. Ding, S. Chen, E. A. Rundensteiner, J. Tatemura, W.-P. Hsiung, and K. S. Candan. Runtime semantic query optimization for event stream processing. In ICDE, pages 676--685, 2008. Google ScholarDigital Library
- D. M. Eyers, L. Vargas, J. Singh, K. Moody, and J. Bacon. Relational database support for event-based middleware functionality. In DEBS, pages 160--171, 2010. Google ScholarDigital Library
- P. Kam and A. W. Fu. Discovering temporal patterns for interval-based events. In DaWaK, pages 317--326, 2000. Google ScholarDigital Library
- J. Kang, J. F. Naughton, and S. D. Viglas. Evaluating window joins over unbounded streams. In ICDE, pages 341--352, March 2003.Google ScholarCross Ref
- D. Kozen. Automata and computability. In W.H.Freeman and Company, New York, 2003. Google ScholarDigital Library
- M. Li, M. Mani, E. A. Rundensteiner, and T. Lin. Constraint-aware complex event pattern detection over streams. In DASFAA, pages 199--215, 2010. Google ScholarDigital Library
- M. Li, M. Mani, E. A. Rundensteiner, D. Wang, and T. Lin. Interval event stream processing. In DEBS, 2009. Google ScholarDigital Library
- M. Liu, M. Li, D. Golovnya, E. A. Rundensteiner, and K. T. Claypool. Sequence pattern query processing over out-of-order event streams. In ICDE, pages 784--795, 2009. Google ScholarDigital Library
- B. Nebel and H.-J. Burckert. Reasoning about temporal relations: A maximal tractable subclass of allen's interval algebra. In AAAI, pages 356--361, 1994. Google ScholarDigital Library
- B. Nebel and H.-J. Burckert. Reasoning about temporal relations: A maximal tractable subclass of allen's interval algebra. J. ACM, 42(1):43--66, 1995. Google ScholarDigital Library
- A. Paschke and P. Vincent. A reference architecture for event processing. In DEBS, 2009. Google ScholarDigital Library
- D. Patel, W. Hsu, and M. Lee. Mining relationships among interval-based events for classification. In SIGMOD, pages 393--404, 2008. Google ScholarDigital Library
- G. Rosu and S. Bensalem. Allen linear (interval) temporal logic - translation to ltl and monitor synthesis. In CAV, pages 263--277, 2006. Google ScholarDigital Library
- E. A. Rundensteiner, L. Ding, T. Sutherland, Y. Zhu, B. Pielech, and N. Mehta. Cape: Continuous query engine with heterogeneous-grained adaptivity. In VLDB, pages 1353--1356, 2004. Google ScholarDigital Library
- D. Toman. Point vs. interval-based query languages for temporal databases. In PODS, pages 58--67, 1996. Google ScholarDigital Library
- E. Wu, Y. Diao, and S. Rizvi. High-performance complex event processing over streams. In SIGMOD, pages 407--418, 2006. Google ScholarDigital Library
- S. Wu and Y. Chen. Mining nonambiguous temporal patterns for interval-based events. IEEE Trans. Knowl. Data Eng., 19(6):742--758, 2007. Google ScholarDigital Library
- H. Zhang, Y. Diao, and N. Immerman. Recognizing patterns in streams with imprecise timestamps. PVLDB, 3(1):244--255, 2010. Google ScholarDigital Library
Index Terms
- Complex event pattern detection over streams with interval-based temporal semantics
Recommendations
Temporal constraints for rule-based event processing
PIKM '07: Proceedings of the ACM first Ph.D. workshop in CIKMComplex event processing (CEP) is an important technology for event-driven systems with a broad application space ranging from supply chain management for RFID, systems monitoring, and stock market analysis to news services. The purpose of CEP is the ...
Detection of complex temporal patterns over data streams
Special issue: ADBIS 2002: Advances in databases and information systemsA growing number of applications require support for processing data that is in the form of continuous stream rather than finite stored data. For instance, network and traffic management, medical monitoring are some of the new applications that ...
TPStream: low-latency and high-throughput temporal pattern matching on event streams
AbstractSequential pattern matching to detect a user-defined sequence of conditions on event streams is a key feature in modern event processing systems. However, the sequential nature of event based pattern matching has two major deficiencies. First, it ...
Comments