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QoS Aggregation in Web Service Compositions

Authors: Michael C. Jaeger; Gregor Rojec-Goldmann; Gero Mühl;

QoS Aggregation in Web Service Compositions

Abstract

For the composition of Web services non-functional characteristics are commonly considered criteria for finding and selecting available services. Our work focuses on a mechanism that determines the overall quality-of-service (QoS) of a composition by aggregating the QoS of the individual services. With aggregated QoS it can be verified whether a set of services satisfies the QoS requirements for the whole composition or not. The aggregation performed builds upon abstract composition patterns, which model basic structural elements of a composition like parallel paths, a sequence, or a looped execution. In this work we extend existing composition patterns with the abilities to consider dependencies between services. Furthermore we introduce, how to use the pattern-based aggregation in the monitoring process during run-time. We explain how the data derived from the monitoring process can be used to calculate a more accurate aggregation of QoS for the composition.

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    influence
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Powered by OpenAIRE graph
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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!
57
Average
Top 1%
Top 10%
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