Continuous queries over data streams
ACM SIGMOD Record
Composite Event Specification in Active Databases: Model & Implementation
VLDB '92 Proceedings of the 18th International Conference on Very Large Data Bases
Expressing and optimizing sequence queries in database systems
ACM Transactions on Database Systems (TODS)
Processing XML streams with deterministic automata and stream indexes
ACM Transactions on Database Systems (TODS)
High-performance complex event processing over streams
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Introduction to Automata Theory, Languages, and Computation (3rd Edition)
Introduction to Automata Theory, Languages, and Computation (3rd Edition)
Event Stream Processing with Out-of-Order Data Arrival
ICDCSW '07 Proceedings of the 27th International Conference on Distributed Computing Systems Workshops
Efficient pattern matching over event streams
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Automaton in or out: run-time plan optimization for XML stream processing
SSPS '08 Proceedings of the 2nd international workshop on Scalable stream processing system
An algorithmic approach to event summarization
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
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Event stream processing, where we detect patterns on incoming event streams, has tremendous value in early determination of critical conditions, enabling on-time response for several important applications. Event stream processing has two significant differences from prior work on XML/relational stream processing: ambiguous events, where an event can match multiple query symbols/conditions in the pattern; and negation, used in event stream processing patterns to specify the non-occurrence of a pattern. In this paper, we develop a formal framework to define the semantics of event patterns, including negation, and describe how to construct a deterministic finite state automaton even in the presence of ambiguous events. Using our framework, we can construct an efficient deterministic finite state automaton for detecting patterns with any complex nesting of negations over an event stream which may have ambiguous events. Our preliminary experimental studies illustrate the significant benefits of our approach to existing approaches.