Supporting valid-time indeterminacy
ACM Transactions on Database Systems (TODS)
Expressing and optimizing sequence queries in database systems
ACM Transactions on Database Systems (TODS)
Flexible time management in data stream systems
PODS '04 Proceedings of the twenty-third ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
High-performance complex event processing over streams
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Using magpie for request extraction and workload modelling
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
What is "next" in event processing?
Proceedings of the twenty-sixth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Efficient query evaluation on probabilistic databases
The VLDB Journal — The International Journal on Very Large Data Bases
BorderPatrol: isolating events for black-box tracing
Proceedings of the 3rd ACM SIGOPS/EuroSys European Conference on Computer Systems 2008
Efficient pattern matching over event streams
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Event queries on correlated probabilistic streams
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Using Punctuation Schemes to Characterize Strategies for Querying over Data Streams
IEEE Transactions on Knowledge and Data Engineering
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
Probabilistic Inference over RFID Streams in Mobile Environments
ICDE '09 Proceedings of the 2009 IEEE 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
ZStream: a cost-based query processor for adaptively detecting composite events
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
Microsoft CEP server and online behavioral targeting
Proceedings of the VLDB Endowment
Determining the currency of data
Proceedings of the thirtieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Complex event processing over unreliable RFID data streams
APWeb'11 Proceedings of the 13th Asia-Pacific web conference on Web technologies and applications
Towards proactive event-driven computing
Proceedings of the 5th ACM international conference on Distributed event-based system
Complex pattern ranking (CPR): evaluating top-k pattern queries over event streams
Proceedings of the 5th ACM international conference on Distributed event-based system
Complex event pattern detection over streams with interval-based temporal semantics
Proceedings of the 5th ACM international conference on Distributed event-based system
OECEP: enriching complex event processing with domain knowledge from ontologies
Proceedings of the Fifth Balkan Conference in Informatics
Determining the Currency of Data
ACM Transactions on Database Systems (TODS)
An event-oriented inference algorithm with timing constraints
Proceedings of the 2012 ACM Research in Applied Computation Symposium
RTRS: a novel real-time reasoning system based on active rules
ACM SIGAPP Applied Computing Review
Complex event processing over distributed probabilistic event streams
Computers & Mathematics with Applications
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Large-scale event systems are becoming increasingly popular in a variety of domains. Event pattern evaluation plays a key role in monitoring applications in these domains. Existing work on pattern evaluation, however, assumes that the occurrence time of each event is known precisely and the events from various sources can be merged into a single stream with a total or partial order. We observe that in real-world applications event occurrence times are often unknown or imprecise. Therefore, we propose a temporal model that assigns a time interval to each event to represent all of its possible occurrence times and revisit pattern evaluation under this model. In particular, we propose the formal semantics of such pattern evaluation, two evaluation frameworks, and algorithms and optimizations in these frameworks. Our evaluation results using both real traces and synthetic systems show that the event-based framework always outperforms the point-based framework and with optimizations, it achieves high efficiency for a wide range of workloads tested.