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SERSCIS-Ont: A Formal Metrics Model for Adaptive Service Oriented Frameworks

Authors: Surridge, Mike; Chakravarthy, Ajay; Bashevoy, Maxim; Hall-May, Martin;

SERSCIS-Ont: A Formal Metrics Model for Adaptive Service Oriented Frameworks

Abstract

In the Future Internet, programs will run on a dynamically changing collection of services, entailing the consumption of a more complex set of resources including financial resources. The von Neumann model offers no useful abstractions for such resources, even with refinements to address parallel and distributed computing devices. In this paper we detail the specification for a post-von Neumann model of metrics where program performance and resource consumption can be quantified and encoding of the behaviour of processes that use these resources is possible. Our approach takes a balanced view between service provider and service consumer requirements, supporting service management and protection as well as non-functional specifications for service discovery and composition.

Country
United Kingdom
Related Organizations
Keywords

adaptive metrics, SOA, measurements, constraints, QoS

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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!
0
Average
Average
Average
Green