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NEEL: The Nested Complex Event Language for Real-Time Event Analytics

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Book cover Enabling Real-Time Business Intelligence (BIRTE 2010)

Abstract

Complex event processing (CEP) over event streams has become increasingly important for real-time applications ranging from health care, supply chain management to business intelligence. These monitoring applications submit complex event queries to track sequences of events that match a given pattern. As these systems mature the need for increasingly complex nested sequence query support arises, while the state-of-art CEP systems mostly support the execution of only flat sequence queries. In this paper, we introduce our nested CEP query language NEEL for expressing nested queries composed of sequence, negation, AND and OR operators. Thereafter, we also define its formal semantics. Subtle issues with negation and predicates within the nested sequence context are discussed. An E-Analytics system for processing nested CEP queries expressed in the NEEL language has been developed. Lastly, we demonstrate the utility of this technology by describing a case study of applying this technology to a real-world application in health care.

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References

  1. Wu, E., Diao, Y., Rizvi, S.: High-performance complex event processing over streams. In: SIGMOD Conference, pp. 407–418 (2006)

    Google Scholar 

  2. 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)

    Google Scholar 

  3. Boyce, J.M., Pittet, D.: Guideline for hand hygiene in healthcare settings. MMWR Recomm Rep. 51, 1–45 (2002)

    Google Scholar 

  4. Shnayder, V., Chen, B., Lorincz, K., Fulford-Jones, T.R.F., Welsch, M.: Sensor Networks for Medical Care. In Harvard University Technical Report TR-08-05 (2005)

    Google Scholar 

  5. Stankovic, J.A., Cao, Q., et al.: Wireless sensor networks for in-home healthcare: Potential and challenges. In: Proceedings of HCMDSS Workshop (2005)

    Google Scholar 

  6. Barga, R.S., Goldstein, J., Ali, M., Hong, M.: Consistent streaming through time: A vision for event stream processing. In: CIDR, pp. 363–374 (2007)

    Google Scholar 

  7. Chakravarthy, S., Krishnaprasad, V., Anwar, E., Kim, S.K.: Composite events for active databases: Semantics, contexts and detection. In: VLDB, pp. 606–617 (1994)

    Google Scholar 

  8. Gupta, C., Wang, S., Ari, I., Hao, M., Dayal, U., Mehta, A., Marwah, M., Sharma, R.: Chaos: A data stream analysis architecture for enterprise applications. In: CEC 2009, pp. 33–40 (2009)

    Google Scholar 

  9. Inetats, I.: Stock trade traces, http://www.inetats.com/

  10. Seshadri, P., Pirahesh, H., Leung, T.Y.C.: Complex query decorrelation. In: ICDE, pp. 450–458 (1996)

    Google Scholar 

  11. Beeri, C., Ramakrishnan, R.: On the Power of Magic. J. Log. Program. 10, 255–299 (1991)

    Article  MathSciNet  MATH  Google Scholar 

  12. Wong, E., Youssefi, K.: Decomposition - a strategy for query processing. ACM Trans. Database Syst. 1(3), 223–241 (1976)

    Article  Google Scholar 

  13. Smith, J.M., Chang, P.Y.-T.: Optimizing the performance of a relational algebra database interface. Commun. ACM 18(10), 568–579 (1975)

    Article  MATH  Google Scholar 

  14. Guravannavar, R., Ramanujam, H.S., Sudarshan, S.: Optimizing nested queries with parameter sort orders. In: VLDB, pp. 481–492 (2005)

    Google Scholar 

  15. Seshadri, P., Pirahesh, H., Leung, T.Y.C.: Complex query decorrelation. In: ICDE, pp. 450–458. IEEE Computer Society, Los Alamitos (1996)

    Google Scholar 

  16. Liu, M., Ray, M., Rundensteiner, E., Dougherty, D., et al.: Processing strategies for nested complex sequence pattern queries over event streams. In: 7th International Workshop on Data Management for Sensor Networks (DMSN 2010), pp. 14–19 (2010)

    Google Scholar 

  17. Wang, D., Rundensteiner, E., Ellison III, R.: Active complex event processing: applications in realtime health care. In: VLDB (2010) (demonstration paper)

    Google Scholar 

  18. Zhu, D., Sethi, A.S.: SEL - A new event pattern specification language for event correlation. In: Proc. ICCCN 2001, Tenth International Conference on Computer Communications and Networks, pp. 586–589 (2001)

    Google Scholar 

  19. Gehani, N.H., Jagadish, H.V., Shmueli, O.: Composite event specification in active databases: model & implementation. In: VLDB 1992, pp. 327–338 (1992)

    Google Scholar 

  20. Chakravarthy, S., Krishnaprasad, V., et al.: Composite events for active databases: semantics, contexts and detection. In: VLDB 1994, pp. 606–617 (1994)

    Google Scholar 

  21. Diao, Y., Immerman, N., Gyllstrom, D.: SASE+: An Agile Language for Kleene Closure over Event Streams, UMass Technical Report 07-03

    Google Scholar 

  22. Greco, S., Sacca, D., Zaniolo, C.: Datalog queries with stratified negation and choice. In: Vardi, M.Y., Gottlob, G. (eds.) ICDT 1995. LNCS, vol. 893, pp. 82–96. Springer, Heidelberg (1995)

    Chapter  Google Scholar 

  23. Liu, M., Rundensteiner, E.A., Greenfield, K., Gupta, C., Wang, S., Ari, I., Mehta, A.: E-Cube: Multi-dimensional event sequence processing using concept and pattern hierarchies. In: ICDE 2010, pp. 1097–1100 (2010)

    Google Scholar 

  24. Wang, D., Rundensteiner, E.A., Ellison, R., Wang, H.: Active Complex Event Processing: Applications in Real-Time Health Care. In: PVLDB, pp. 1545–1548 (2010)

    Google Scholar 

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Liu, M. et al. (2011). NEEL: The Nested Complex Event Language for Real-Time Event Analytics. In: Castellanos, M., Dayal, U., Markl, V. (eds) Enabling Real-Time Business Intelligence. BIRTE 2010. Lecture Notes in Business Information Processing, vol 84. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22970-1_9

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  • DOI: https://doi.org/10.1007/978-3-642-22970-1_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-22969-5

  • Online ISBN: 978-3-642-22970-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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