Models and issues in data stream systems
Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Automata and Computability
Continuous queries over data streams
ACM SIGMOD Record
Aurora: a new model and architecture for data stream management
The VLDB Journal — The International Journal on Very Large Data Bases
High-performance complex event processing over streams
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Semantic approach to event processing
Proceedings of the 2007 inaugural international conference on Distributed event-based systems
XMark: a benchmark for XML data management
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Plan-based complex event detection across distributed sources
Proceedings of the VLDB Endowment
Runtime Semantic Query Optimization for Event Stream Processing
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Sequence Pattern Query Processing over Out-of-Order Event Streams
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
E-Tec: A Constraint-Aware Query Engine for Pattern Detection over Event Streams
ICSC '09 Proceedings of the 2009 IEEE International Conference on Semantic Computing
Complex event pattern detection over streams with interval-based temporal semantics
Proceedings of the 5th ACM international conference on Distributed event-based system
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In this paper, we propose a framework for constraint-aware pattern detection over event streams. Given the constraint of the input streams, our proposed framework on the fly checks the query satisfiability / unsatisfiability using a lightweight reasoning mechanism. Based on the constraint specified in the input stream, we are able to adjust the processing strategy dynamically, by producing early feedbacks, releasing unnecessary system resources and terminating corresponding pattern monitor, thus effectively decreasing the resource consumption and expediting the system response on certain situations. Our experimental study illustrates the significant performance improvement achieved by the constraint-aware pattern detection framework with little overhead.