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International Conference on Web-Age Information Management

WAIM 2016: Web-Age Information Management pp 125–136Cite as

Efficient Context-Aware Nested Complex Event Processing over RFID Streams

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9998))

Abstract

With large scale of utilization of monitoring devices such as RFID, sensors and mobile phones, events are generated in a high-speed fashion. Decisions should be made in real time during business processes. Complex Event Processing (CEP) has become increasingly important for tracking and monitoring anomalies and trends in event streams. Nested event detection of RFID event stream is one of the most import class of queries. Current optimization of nested RFID event detection mainly considers caching intermediate results to reduce re-computation of similar results for nested subexpression. In this paper, we use context information of an RFID scenario to optimize nested event detection. We formalize context of an RFID scenario as spatial and temporal constraints and transform these constraints into rules over a nested NFA. Further, we present rewriting context rules to optimize nested event query plan. Experimental results show that with context information introduced, response time had been reduced greatly compared with counterpart methods.

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Author information

Authors and Affiliations

  1. School of Information Science and Technology, Southwest Jiaotong University, Chengdu, 610031, China

    Shanglian Peng

  2. College of Computer Science, Chengdu University of Information Technology, Chengdu, 610225, China

    Shanglian Peng & Jia He

Authors
  1. Shanglian Peng
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  2. Jia He
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Corresponding author

Correspondence to Shanglian Peng .

Editor information

Editors and Affiliations

  1. Tsinghua University , Beijing, China

    Shaoxu Song

  2. Beihang University , Beijing, China

    Yongxin Tong

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Peng, S., He, J. (2016). Efficient Context-Aware Nested Complex Event Processing over RFID Streams. In: Song, S., Tong, Y. (eds) Web-Age Information Management. WAIM 2016. Lecture Notes in Computer Science(), vol 9998. Springer, Cham. https://doi.org/10.1007/978-3-319-47121-1_11

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  • DOI: https://doi.org/10.1007/978-3-319-47121-1_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-47120-4

  • Online ISBN: 978-3-319-47121-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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