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Aggressive Complex Event Processing with Confidence over Out-of-Order Streams

Aggressive Complex Event Processing with Confidence over Out-of-Order Streams
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摘要 In recent years, there has been a growing need for complex event processing (CEP), ranging from supply chain management to security monitoring. In many scenarios events are generated in different sources but arrive at the central server out of order, due to the differences of network latencies. Most state-of-the-art techniques process out-of-order events by buffering the events until the total event order within a specified range can be guaranteed. Their main problems are leading to increasing response time and reducing system throughput. This paper aims to build a high performance out-of- order event processing mechanism, which can match events as soon as they arrive instead of buffering them till all arrive. A suffix-automaton-based event matching algorithm is proposed to speed up query processing, and a confidence-based accuracy evaluation is proposed to control the query result quality. The performance of our approach is evaluated through detailed accuracy and response time analysis. As experimental results show, our approach can obviously speed up the query matching time and produce reasonable query results. In recent years, there has been a growing need for complex event processing (CEP), ranging from supply chain management to security monitoring. In many scenarios events are generated in different sources but arrive at the central server out of order, due to the differences of network latencies. Most state-of-the-art techniques process out-of-order events by buffering the events until the total event order within a specified range can be guaranteed. Their main problems are leading to increasing response time and reducing system throughput. This paper aims to build a high performance out-of- order event processing mechanism, which can match events as soon as they arrive instead of buffering them till all arrive. A suffix-automaton-based event matching algorithm is proposed to speed up query processing, and a confidence-based accuracy evaluation is proposed to control the query result quality. The performance of our approach is evaluated through detailed accuracy and response time analysis. As experimental results show, our approach can obviously speed up the query matching time and produce reasonable query results.
出处 《Journal of Computer Science & Technology》 SCIE EI CSCD 2011年第4期685-696,共12页 计算机科学技术学报(英文版)
基金 supported by the National Natural Science Foundation of China under Grant Nos.61003058,60933001 the Fundamental Research Funds for the Central Universities under Grant No.N090104001
关键词 complex event processing (CEP) out-of-order suffix-automaton searching-table complex event processing (CEP), out-of-order, suffix-automaton, searching-table
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参考文献23

  • 1Chakravarthy S, Krishnaprasad V, Anwar E, Kim S K. Com- posite events for active databases: Semantics, contexts and detection. In Proc. VLDB, Santiago de Chile, Chile, Sept. 12- 15, 1994, pp.606-617.
  • 2Re C, Letchner J, Balazinska M, Suciu D. Event queries on correlated probabilistic streams. In Proc. SIGMOD, Vancou- ver, Canada, Jun. 10-12, 2008, pp.715-728.
  • 3Liu M, Li M, Golovnya D, Rundensteiner E A, Claypoo K. Sequence pattern query processing over out-of-order event streams. In Proc. ICDE, Shanghai, China, Mar. 29-Apr. 2, 2009, pp.784-795.
  • 4Wu E, Diao Y, Rizvi S. High-performance complex event pro- cessing over streams. In Proc. SIGMOD, Chicago, USA, Jun. 27-29, 2006, pp.407-418.
  • 5Barga R S, Goldstein J, Ali M, Hong M. Consistent streaming through time: A vision for event stream processing. In Proc. CIDR, Asilomax, USA, Jan. 7-10, 2007, pp.363-374.
  • 6Gyllstrom D, Agrawal J, Diao Y, Immerman N. On support- ing kleene closure over event streams. In Proc. ICDE, Can- cun, Mexico, Apr. 7-12, 2008, pp.1391-1393.
  • 7Demers A, Gehrke J, Panda B, Riedewald M, Sharma V, White W. Cayuga: A general purpose event monitoring sys- tem. In Proc. CIDR, Asilomar, USA, 2007, pp.412-422.
  • 8Abadi D, Carney D, Cetintemel U et al. Aurora: A data stream management system. In Proc. the 2003 ACM SIG- MOD International Conference on Management of Data, San Diego, USA, Jun. 9-12, 2003, pp.666-677.
  • 9Babu S, Srivastava U, Widom J. Exploiting k-constraints to reduce memory overhead in continuous queries over data streams. IEEE Trans. Knowl. Data Eng., 2003, 13(3): 545- 580.
  • 10Tucker P A, Maie D, Sheard T, Fegaras L. Exploiting punc- tuation semantics in continuous data streams. TKDE, 2003, 15(3): 555-568.

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