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Process Models for Distributed Event-Based Systems.

Authors: Blanco, Rolando Maldonado;

Process Models for Distributed Event-Based Systems.

Abstract

Distributed Event-Based Systems (DEBSs) are middleware supporting the interaction of publisher and subscriber components via events. In DEBSs, the subscribers to be notified when an event is announced are decided at run-time without requiring publisher components to know the name or locations of the subscribers, nor the subscribers to know the name or locations of the publishers. This low coupling between components makes DEBSs suitable for applications with a large or unpredictable number of autonomous components. The development of applications in DEBSs is an ad hoc process poorly supported by current software engineering methodologies. Moreover, the behaviours exhibited by these systems and their applications are not well understood, and no suitable models exist where these behaviours can be described and analyzed. The main concern of this thesis is the development of such models. Specifically, we develop formalisms and models supporting the specification, prediction, and validation of the behaviour exhibited by the middleware and the applications executing on it. Our main contributions to the area are: new formalisms for the representation of DEBSs and their applications, and for the specification of both, system and application properties; a categorization of the features related to the definition, announcement, and notification of events in DEBSs and, in general, event-based systems; models representing the categorized DEBS features; case studies detailing models and properties for specific systems; a prototype tool for the verification of DEBSs and applications. The formalisms developed expose the location of the actions in the modelled systems and support the specification of several forms of location-awareness and adaptive behaviour.

Country
Canada
Related Organizations
Keywords

Computer Science, 004

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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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