Event composition in time-dependent distributed systems

Liebig, Christoph; Cilia, Mariano; Buchmann, Alejandro

doi:10.1109/coopis.1999.792159

Cited by 58 publications

(48 citation statements)

References 33 publications

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“…As a result, if two nodes detect events A and B respectively, it may be impossible to decide which occurred first. An interval timestamp, consisting of a start time and an end time, can make this ambiguity explicit, yet remains consistent with the physical time order of the events [14].…”

Section: A1 Definition Of Interval Timestampsmentioning

confidence: 99%

“…Under a guaranteed detection policy, an event is consumed from an event input stream only once it has become stable 1 [14]. The consumption of only stable events ensures that no spurious composite events are detected.…”

Section: Best-effort Detectionmentioning

confidence: 99%

“…The partial order of timestamps in a distributed system is made explicit by having timestamps associated with an uncertainty interval. A CORBA-based detection architecture is presented in [14] that implements this time model. The notion of event stability is defined in order to handle communication delays.…”

Section: Related Workmentioning

confidence: 99%

“…In our CE detection framework, we adopt the interval timestamp model introduced in [14]. The partial order of timestamps in a distributed system is made explicit by having timestamps associated with an uncertainty interval.…”

Section: Related Workmentioning

confidence: 99%

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A Framework for Event Composition in Distributed Systems

Pietzuch

Shand

Bacon

2003

Lecture Notes in Computer Science

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Abstract. For large-scale distributed applications such as internet-wide or ubiquitous systems, event-based communication is an effective messaging mechanism between components. In order to handle the large volume of events in such systems, composite event detection enables application components to express interest in the occurrence of complex patterns of events. In this paper, we introduce a general composite event detection framework that can be added on top of existing middleware architectures -as demonstrated in our implementation over JMS. We argue that the framework is flexible, expressive, and easy to implement. Based on finite state automata extended with a rich time model and support for parameterisation, it provides a decomposable core language for composite event specification, so that composite event detection can be distributed throughout the system. We discuss the issues associated with automatic distribution of composite event expressions. Finally, tests of our composite event system over JMS show reduced bandwidth consumption and a low notification delay for composite events.

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Section: A1 Definition Of Interval Timestampsmentioning

confidence: 99%

Section: Best-effort Detectionmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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A Framework for Event Composition in Distributed Systems

Pietzuch

Shand

Bacon

2003

Lecture Notes in Computer Science

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“…Time-sensitive CEP queries and event composition often rely on synchronized time measurements among the producers, to retain either absolute time difference or relative order of events [40]. In our model, time is expressed as a special case of the EPA state, which is periodically changed (irrespective of event inputs) and shared among the EPAs.…”

Section: Faults In Complex Event Processingmentioning

confidence: 99%

Deriving a unified fault taxonomy for event-based systems

Hummer

Inzinger

Leitner

et al. 2012

Proceedings of the 6th ACM International Conference on Distributed Event-Based Systems

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Dependability and fault-tolerance, which are key requirements for business-or safety-critical applications, require explicit knowledge of potential faults that may occur within a system. In contrast to other major research directions, the emerging field of distributed event-based systems is yet lacking a common understanding of faults. In this paper we take a step forward and study potential origins and effects of faults in such systems. Our work on a unified fault taxonomy follows a rigorous methodology. We first identify five core sub-areas in the broader field of event-based systems, and discuss commonalities and differences among them. Then we derive from the existing literature a coherent domain model, which accurately captures the specifics of the different areas. The domain model provides a holistic view and covers both structural and procedural aspects of event-based systems. Based on this model, we elaborate a detailed taxonomy of faults, in line with well-established fault dimensions from dependable and secure computing. The fault taxonomy forms the basis for a comprehensive discussion of fault instances across the five sub-areas of event processing.

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