Snoop: an expressive event specification language for active databases
Data & Knowledge Engineering
The Power of Events: An Introduction to Complex Event Processing in Distributed Enterprise Systems
The Power of Events: An Introduction to Complex Event Processing in Distributed Enterprise Systems
Active Database Systems: Triggers and Rules for Advanced Database Processing
Active Database Systems: Triggers and Rules for Advanced Database Processing
Expressiveness Issues and Decision Problems for Active Database Event Queries
ICDT '01 Proceedings of the 8th International Conference on Database Theory
Composite Events for Active Databases: Semantics, Contexts and Detection
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Two Approaches to Event Definition
DEXA '02 Proceedings of the 13th International Conference on Database and Expert Systems Applications
On the Semantics of Complex Events in Active Database Management Systems
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
The VLDB Journal — The International Journal on Very Large Data Bases
An event detection algebra for reactive systems
Proceedings of the 4th ACM international conference on Embedded software
NFMi: An Inter-domain Network Fault Management System
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Exploiting predicate-window semantics over data streams
ACM SIGMOD Record
High-performance complex event processing over streams
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
The CQL continuous query language: semantic foundations and query execution
The VLDB Journal — The International Journal on Very Large Data Bases
SnoopIB: interval-based event specification and detection for active databases
Data & Knowledge Engineering
Cayuga: a high-performance event processing engine
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
MavEStream: Synergistic Integration of Stream and Event Processing
ICDT '07 Proceedings of the Second International Conference on Digital Telecommunications
Monitoring streams: a new class of data management applications
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Events and streams: harnessing and unleashing their synergy!
Proceedings of the second international conference on Distributed event-based systems
Stream Data Processing: A Quality of Service Perspective Modeling, Scheduling, Load Shedding, and Complex Event Processing
A continuous workflow scheduling framework
Proceedings of the 2nd ACM SIGMOD Workshop on Scalable Workflow Execution Engines and Technologies
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For a number of stream applications, synergistic integration of stream as well as event processing is becoming a necessity. However, the relationship between windows and consumption modes has not been studied in the literature. A clear understanding of this relationship is important for integrating the two synergistically as well as detecting meaningful complex events using events generated by a stream processing system. In this paper, we analyze the notion of windows introduced for stream processing and the notion of consumption modes introduced for event processing. Based on the analysis, this paper proposes several approaches for combining the two and investigates their ramifications. We present conclusions based on our analysis and an integrated architecture that currently supports one of the reconciled approaches.