distributed event processing
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Context-Awareness in Task Automation Services by Distributed Event Processing

Lecture Notes in Computer Science - Web Information Systems Engineering – WISE 2014 Workshops ◽

10.1007/978-3-319-20370-6_15 ◽

2015 ◽

pp. 190-203

Author(s):

Miguel Coronado ◽

Ralf Bruns ◽

Jürgen Dunkel ◽

Sebastian Stipković

Keyword(s):

Context Awareness ◽

Event Processing ◽

Distributed Event Processing

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Distributed Event Processing for Goal-Oriented Workflows

Intelligent Distributed Computing VIII - Studies in Computational Intelligence ◽

10.1007/978-3-319-10422-5_7 ◽

2015 ◽

pp. 49-58

Author(s):

Kai Jander ◽

Lars Braubach ◽

W. Lamersdorf

Keyword(s):

Event Processing ◽

Distributed Event Processing

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In-network real-time performance monitoring with distributed event processing

2014 IEEE Network Operations and Management Symposium (NOMS) ◽

10.1109/noms.2014.6838384 ◽

2014 ◽

Cited By ~ 2

Author(s):

Masanori Miyazawa ◽

Michiaki Hayashi

Keyword(s):

Real Time ◽

Performance Monitoring ◽

Event Processing ◽

Time Performance ◽

Distributed Event Processing

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Dynamic Low-Latency Distributed Event Processing of Sensor Data Streams

PARS Parallel-Algorithmen -Rechnerstrukturen und -Systemsoftware ◽

10.1007/bf03354233 ◽

2013 ◽

Vol 30 (1) ◽

pp. 5-14

Author(s):

Christopher Mutschler ◽

Michael Philippsen

Keyword(s):

Data Streams ◽

Sensor Data ◽

Low Latency ◽

Event Processing ◽

Distributed Event Processing

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Rollback-recovery without checkpoints in distributed event processing systems

Proceedings of the 7th ACM international conference on Distributed event-based systems - DEBS '13 ◽

10.1145/2488222.2488259 ◽

2013 ◽

Cited By ~ 22

Author(s):

Boris Koldehofe ◽

Ruben Mayer ◽

Umakishore Ramachandran ◽

Kurt Rothermel ◽

Marco Völz

Keyword(s):

Event Processing ◽

Rollback Recovery ◽

Distributed Event Processing

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Understanding and improving the cost of scaling distributed event processing

Proceedings of the 6th ACM International Conference on Distributed Event-Based Systems - DEBS '12 ◽

10.1145/2335484.2335516 ◽

2012 ◽

Cited By ~ 5

Author(s):

Shoaib Akram ◽

Manolis Marazakis ◽

Angelos Bilas

Keyword(s):

Event Processing ◽

The Cost ◽

Distributed Event Processing

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Accurate latency estimation in a distributed event processing system

2011 IEEE 27th International Conference on Data Engineering ◽

10.1109/icde.2011.5767926 ◽

2011 ◽

Cited By ~ 9

Author(s):

Badrish Chandramouli ◽

Jonathan Goldstein ◽

Roger Barga ◽

Mirek Riedewald ◽

Ivo Santos

Keyword(s):

Processing System ◽

Event Processing ◽

Distributed Event Processing

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Distributed event processing for activity recognition

Proceedings of the 5th ACM international conference on Distributed event-based system - DEBS '11 ◽

10.1145/2002259.2002315 ◽

2011 ◽

Cited By ~ 2

Author(s):

Visalakshmi Suresh ◽

Paul Ezhilchelvan ◽

Paul Watson ◽

Cuong Pham ◽

Dan Jackson ◽

...

Keyword(s):

Activity Recognition ◽

Event Processing ◽

Distributed Event Processing

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Proceedings of the First International Workshop on Algorithms and Models for Distributed Event Processing - AlMoDEP '11

10.1145/2031792 ◽

2011 ◽

Keyword(s):

International Workshop ◽

Event Processing ◽

Distributed Event Processing

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StreamMine

Principles and Applications of Distributed Event-Based Systems - Advances in Systems Analysis, Software Engineering, and High Performance Computing ◽

10.4018/978-1-60566-697-6.ch011 ◽

2010 ◽

pp. 260-283

Author(s):

Christof Fetzer ◽

Andrey Brito ◽

Robert Fach ◽

Zbigniew Jerzak

Keyword(s):

Transactional Memory ◽

Processing System ◽

Speculative Execution ◽

Event Processing ◽

Software Transactional Memory ◽

Time Stamp ◽

Ordering Constraints ◽

Large Clusters ◽

Application Specific ◽

Distributed Event Processing

StreamMine is a novel distributed event processing system that we are currently developing. It is architected for running on large clusters and uses content-based publish/subscribe middleware for the communication between event processing components. Event processing components need to enforce application-specific ordering constraints, e.g., all events need to be processed in order of some given time stamp. To harness the power of modern multi-core computers, we support the speculative execution of events. Ordering conflicts are detected dynamically and rolled backed using a Software Transactional Memory.

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