Quantifying the Impact of Configuration Space for Elasticity Benchmarking
N. Herbst. Karlsruhe Institute of Technology (KIT), Am Fasanengarten 5, 76131 Karlsruhe, Germany, Study Thesis, (2011)
Zusammenfassung
Elasticity is the ability of a software system to dynamically adapt the amount of the resources it provides to clients as their workloads increase or decrease. In the context of cloud computing, automated resizing of a virtual machine's resources can be considered as a key step towards optimisation of a system's cost and energy efficiency. Existing work on cloud computing is limited to the technical view of implementing elastic systems, and definitions of scalability have not been extended to cover elasticity. This study thesis presents a detailed discussion of elasticity, proposes metrics as well as measurement techniques, and outlines next steps for enabling comparisons between cloud computing offerings on the basis of elasticity. I discuss results of our work on measuring elasticity of thread pools provided by the Java virtual machine, as well as an experiment setup for elastic CPU time slice resizing in a virtualized environment. An experiment setup is presented as future work for dynamically adding and removing z/VM Linux virtual machine instances to a performance relevant group of virtualized servers.
%0 Thesis
%1 Herbst2011a
%A Herbst, Nikolas Roman
%C Am Fasanengarten 5, 76131 Karlsruhe, Germany
%D 2011
%K Cloud Elasticity Metrics_and_benchmarking_methodologies Virtualization descartes t_studentthesis
%T Quantifying the Impact of Configuration Space for Elasticity Benchmarking
%X Elasticity is the ability of a software system to dynamically adapt the amount of the resources it provides to clients as their workloads increase or decrease. In the context of cloud computing, automated resizing of a virtual machine's resources can be considered as a key step towards optimisation of a system's cost and energy efficiency. Existing work on cloud computing is limited to the technical view of implementing elastic systems, and definitions of scalability have not been extended to cover elasticity. This study thesis presents a detailed discussion of elasticity, proposes metrics as well as measurement techniques, and outlines next steps for enabling comparisons between cloud computing offerings on the basis of elasticity. I discuss results of our work on measuring elasticity of thread pools provided by the Java virtual machine, as well as an experiment setup for elastic CPU time slice resizing in a virtualized environment. An experiment setup is presented as future work for dynamically adding and removing z/VM Linux virtual machine instances to a performance relevant group of virtualized servers.
@mastersthesis{Herbst2011a,
abstract = {{Elasticity is the ability of a software system to dynamically adapt the amount of the resources it provides to clients as their workloads increase or decrease. In the context of cloud computing, automated resizing of a virtual machine's resources can be considered as a key step towards optimisation of a system's cost and energy efficiency. Existing work on cloud computing is limited to the technical view of implementing elastic systems, and definitions of scalability have not been extended to cover elasticity. This study thesis presents a detailed discussion of elasticity, proposes metrics as well as measurement techniques, and outlines next steps for enabling comparisons between cloud computing offerings on the basis of elasticity. I discuss results of our work on measuring elasticity of thread pools provided by the Java virtual machine, as well as an experiment setup for elastic CPU time slice resizing in a virtualized environment. An experiment setup is presented as future work for dynamically adding and removing z/VM Linux virtual machine instances to a performance relevant group of virtualized servers.}},
added-at = {2020-04-06T11:28:21.000+0200},
address = {Am Fasanengarten 5, 76131 Karlsruhe, Germany},
author = {Herbst, Nikolas Roman},
biburl = {https://www.bibsonomy.org/bibtex/285891e64b41ea459e7239b366bfa19f7/se-group},
interhash = {a6b784e8f2ba8ddcebf006a9bea377ea},
intrahash = {85891e64b41ea459e7239b366bfa19f7},
keywords = {Cloud Elasticity Metrics_and_benchmarking_methodologies Virtualization descartes t_studentthesis},
school = {{Karlsruhe Institute of Technology (KIT)}},
timestamp = {2020-10-20T11:36:31.000+0200},
title = {{Quantifying the Impact of Configuration Space for Elasticity Benchmarking}},
type = {{Study Thesis}},
year = 2011
}