Semantic Complex Event Processing over End-to-End Data Flows

Emerging Complex Event Processing (CEP) applications in cyber physical systems like Smart Power Grids present novel challenges for end-to-end analysis over events, flowing from heterogeneous information sources to persistent knowledge repositories. CEP for these applications must support two distinctive features – easy specification patterns over diverse information streams, and integrated pattern detection over realtime and historical events. Existing work on CEP has been limited to relational query patterns, and engines that match events arriving after the query has been registered. We propose SCEPter, a semantic complex event processing framework which uniformly processes queries over continuous and archived events. SCEPteris built around an existing CEP engine with innovative support for semantic event pattern specification and allows their seamless detection over past, present and future events. Specifically, we describe a unified semantic query model that can operate over data flowing through event streams to event repositories. Compile-time and runtime semantic patterns are distinguished and addressed separately for efficiency. Query rewriting is examined and analyzed in the context of temporal boundaries that exist between event streams and their repository to avoid duplicate or missing results. The design and prototype implementation of SCEPterare analyzed using latency and throughput metrics for scenarios from the Smart Grid domain.

[1]  Elias Leake Quinn,et al.  Smart Metering and Privacy: Existing Laws and Competing Policies , 2009 .

[2]  N. Shadbolt,et al.  4store: The Design and Implementation of a Clustered RDF Store , 2009 .

[3]  Michael Stonebraker,et al.  Aurora: a data stream management system , 2003, SIGMOD '03.

[4]  Fatos Xhafa,et al.  Special issue on cyber physical systems , 2013, Computing.

[5]  Alain Biem,et al.  IBM infosphere streams for scalable, real-time, intelligent transportation services , 2010, SIGMOD Conference.

[6]  Nenad Stojanovic,et al.  Semantic-based Complex Event Processing in the AAL Domain , 2010, ISWC Posters&Demos.

[7]  Yogesh L. Simmhan,et al.  Towards an inexact semantic complex event processing framework , 2011, DEBS '11.

[8]  Hamid Pirahesh,et al.  Alert: An Architecture for Transforming a Passive DBMS into an Active DBMS , 1991, VLDB.

[9]  Sebastian Rudolph,et al.  Stream reasoning and complex event processing in ETALIS , 2012, Semantic Web.

[10]  Jennifer Widom,et al.  The CQL continuous query language: semantic foundations and query execution , 2006, The VLDB Journal.

[11]  Sharma Chakravarthy,et al.  SnoopIB: Interval-based event specification and detection for active databases , 2003, Data Knowl. Eng..

[12]  Yogesh L. Simmhan,et al.  Improving Energy Use Forecast for Campus Micro-grids Using Indirect Indicators , 2011, 2011 IEEE 11th International Conference on Data Mining Workshops.

[13]  Douglas B. Terry,et al.  Continuous queries over append-only databases , 1992, SIGMOD '92.

[14]  Nesime Tatbul,et al.  Efficiently correlating complex events over live and archived data streams , 2011, DEBS '11.

[15]  Magdalena Balazinska,et al.  Moirae: History-Enhanced Monitoring , 2007, CIDR.

[16]  Johannes Gehrke,et al.  Cayuga: A General Purpose Event Monitoring System , 2007, CIDR.

[17]  Kia Teymourian,et al.  Enabling knowledge-based complex event processing , 2010, EDBT '10.

[18]  Viktor K. Prasanna,et al.  Semantic Information Integration for Smart Grid Applications , 2011 .

[19]  Jennifer Widom,et al.  Set-oriented production rules in relational database systems , 1990, SIGMOD '90.

[20]  Yogesh L. Simmhan,et al.  An Informatics Approach to Demand Response Optimization in Smart Grids , 2011 .

[21]  Martin Kersten,et al.  Exploiting the power of relational databases for efficient stream processing , 2009, EDBT '09.

[22]  Yogesh L. Simmhan,et al.  Semantic Information Modeling for Emerging Applications in Smart Grid , 2012, 2012 Ninth International Conference on Information Technology - New Generations.

[23]  GoldbergDavid,et al.  Continuous queries over append-only databases , 1992 .