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The purpose of the application descriptor is to explicitly describe a set of application-specific parameters that should be tuned by the adaptive framework.
The knowledge is automatically revised during the execution by the adaptive framework by integrating new insights gained from additional runs of the application.
With our approach, those parameters that should be taken into account by the adaptive framework are defined in the environment descriptor and set upon job submission time to improve the behavior of the system for a specific job.
The purpose of the resource descriptor is to explicitly describe a set of computing and storage resource-specific parameters that should be taken into account by the adaptive framework.
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By accessing knowledge about historical jobs, the adaptive framework is able to effect the configuration of a specific job.
The results show that the reduction errors are well controlled by the specified error tolerance, and that the adaptive framework provides significant gains in cost and storage compared to traditional non-adaptive reduction approaches.
The main objective of the adaptive framework is the optimization of the utility for a specific job which is achieved by adaptive configuration of these layers.
Following this scenario, the adaptive job configuration process within the adaptive framework is explained.
The adaptive framework has to monitor multiple resources at the different layers (IaaS, PaaS, SaaS).
The adaptive framework has been designed to manage resources at all three Cloud stack layers involved.
In this section, a prototype implementation of the adaptive framework has been presented.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com