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https://doi.org/10.1...arrow_drop_down
https://doi.org/10.1007/119150...
Part of book or chapter of book . 2006 . Peer-reviewed
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DBLP
Conference object . 2017
Data sources: DBLP
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Scheduling of Composite Web Services

Authors: Dmytro Dyachuk; Ralph Deters;

Scheduling of Composite Web Services

Abstract

Composite Web Services (CWS) aggregate multiple Web Services (WS) in one logical unit to accomplish a complex task (e.g business process) This aggregation is achieved by defining a workflow that orchestrates the underlying Web Services in a manner consistent with the desired functionality Since CWS can aggregate atomic WS and/or other CWS they foster the development of service layers and reuse of already existing functionality An important issue in the deployment of services is their run-time performance under various loads Due to the complex interactions of the underlying services, a CWS they can exhibit problematic and often difficult to predict behaviours in overload situations. This paper focuses on the use of request scheduling for improving CWS performance in overload situations Different scheduling policies are investigated in regards to their effectiveness in helping with bulk arrivals.

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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!
5
Average
Top 10%
Average
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