Conformance Checking and Simulation-based Evolutionary Optimization for Deployment and Reconfiguration of Software in the Cloud

Name: Conformance Checking and Simulation-based Evolutionary Optimization for Deployment and Reconfiguration of Software in the Cloud
Brand: Books on Demand
SKU: 9783732297344
Price: 45.67 EUR
Availability: InStock

Автор: Sören Frey

Език:

Корици: С твърди корици

Издател: Books on Demand

Наличност: Външен склад

Изпращаме след 10-13 дни

45.67 € 89.32 лв

Many SaaS providers nowadays want to leverage the cloud s capabilities also for their existing appli...

Информация за книгата

Автор

Sören Frey

Език

Английски език

Корици

Книга - С твърди корици

Издадена

2014

страници

636

EAN

9783732297344

ISBN

3732297349

Enbook ID

02443913

Издател

Books on Demand

Теглоt

1121

Размери

160 x 226 x 43

Пълно описание

Many SaaS providers nowadays want to leverage the cloud s capabilities also for their existing applications, for example, to enable sound scalability and cost-effectiveness. This thesis provides the approach CloudMIG that supports SaaS providers to migrate those applications to IaaS and PaaS-based cloud environments.§CloudMIG consists of a step-by-step process and focuses on two core components. (1) Restrictions imposed by specific cloud environments (so-called cloud environment constraints (CECs)), such as a limited file system access or forbidden method calls, can be validated by an automatic conformance checking approach. (2) A cloud deployment option (CDO) determines which cloud environment, cloud resource types, deployment architecture, and runtime reconfiguration rules for exploiting a cloud s elasticity should be used. The implied performance and costs can differ in orders of magnitude. CDOs can be automatically optimized with the help of our simulation-based genetic algorithm CDOXplorer.§Extensive lab experiments and an experiment in an industrial context show CloudMIG s applicability and the excellent performance of its two core components.

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Conformance Checking and Simulation-based Evolutionary Optimization for Deployment and Reconfiguration of Software in the Cloud

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