Active Database Systems: Triggers and Rules for Advanced Database Processing
Active Database Systems: Triggers and Rules for Advanced Database Processing
Aurora: a new model and architecture for data stream management
The VLDB Journal — The International Journal on Very Large Data Bases
Operator scheduling in data stream systems
The VLDB Journal — The International Journal on Very Large Data Bases
RFID: Applications, Security, and Privacy
RFID: Applications, Security, and Privacy
High-performance complex event processing over streams
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
ULDBs: databases with uncertainty and lineage
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Introduction to Automata Theory, Languages, and Computation (3rd Edition)
Introduction to Automata Theory, Languages, and Computation (3rd Edition)
Cayuga: a high-performance event processing engine
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Management of probabilistic data: foundations and challenges
Proceedings of the twenty-sixth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Efficient query evaluation on probabilistic databases
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Processing forecasting queries
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
A video stream management system for heterogeneous information integration environments
Proceedings of the 2nd international conference on Ubiquitous information management and communication
On Supporting Kleene Closure over Event Streams
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Probabilistic Event Extraction from RFID Data
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Exploiting Lineage for Confidence Computation in Uncertain and Probabilistic Databases
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Towards expressive publish/subscribe systems
EDBT'06 Proceedings of the 10th international conference on Advances in Database Technology
Integrating a stream processing engine and databases for persistent streaming data management
DEXA'07 Proceedings of the 18th international conference on Database and Expert Systems Applications
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This paper proposes a working framework and a query language to support probabilistic queries for composite event detection over probabilistic event streams. The language allows users to express Kleene closure patterns for complex event detection in the physical world. Our processing method first detects sequence patterns over probabilistic data streams using AIG, a new data structure, which handles active states with a nondeterministic finite automaton (NFA). Our method then computes the probability of each detected sequence pattern based on its lineage. Through the benefit of lineage, the probability of an output event can be directly calculated without taking into account the query plan. An optimised plan can be selected. Finally, we conducted a performance evaluation of our method and compared the results with the original and optimised query plan. The experiment clearly showed that our proposal outperforms straight-forward query plans.