Simulating Cloud Deployment Options for Software Migration Support - Tapa blanda

Fittkau, Florian

 
9783956366963: Simulating Cloud Deployment Options for Software Migration Support
Tapa blanda
ISBN 10: 3956366964 ISBN 13: 9783956366963
Editorial: diplom.de, 2014

Sinopsis

Cloud computing is emerging as a promising new paradigm that aims at delivering computing resources and services on demand. To cope with the frequently found over- and under-provisioning of resources in conventional data centers, cloud computing technologies enable to rapidly scale up and down according to varying workload patterns. However, most software systems are not built for utilizing this so called elasticity and therefore must be adapted during the migration process into the cloud. A challenge during migration is the high number of different possibilities for the deployment to cloud computing resources. For example, there exist a plethora of potential cloud provider candidates. Here, the selection of a specific cloud provider is the most obvious and basic cloud deployment option. Furthermore, the mapping between services and virtual machine instances must be considered when migrating to the cloud and the specific adaptation strategies, like allocating a new virtual machine instance if the CPU utilization is above a given threshold, have to be chosen and configured. The set of combinations of the given choices form a huge design space which is infeasible to test manually. Simulating the different deployment options assists to find the best ratio between high performance and low costs. For this purpose, we developed a simulation tool named CDOSim that can simulate those cloud deployment options. CDOSim integrates into the cloud migration framework CloudMIG Xpress and utilizes KDM models that were extracted by a reverse engineering process. Furthermore, it is possible to use monitored workload profiles as a simulation input. Our evaluation shows that CDOSim's simulation results can support software engineers to sufficiently accurate predict the cost and performance properties of software systems when deployed to private and real world public cloud environments such as Eucalyptus and Amazon EC2, respectively. Thus, CDOSim can be used for the simulation of cloud

"Sinopsis" puede pertenecer a otra edición de este libro.

Reseña del editor

Cloud computing is emerging as a promising new paradigm that aims at delivering computing resources and services on demand. To cope with the frequently found over- and under-provisioning of resources in conventional data centers, cloud computing technologies enable to rapidly scale up and down according to varying workload patterns. However, most software systems are not built for utilizing this so called elasticity and therefore must be adapted during the migration process into the cloud. A challenge during migration is the high number of different possibilities for the deployment to cloud computing resources. For example, there exist a plethora of potential cloud provider candidates. Here, the selection of a specific cloud provider is the most obvious and basic cloud deployment option. Furthermore, the mapping between services and virtual machine instances must be considered when migrating to the cloud and the specific adaptation strategies, like allocating a new virtual machine instance if the CPU utilization is above a given threshold, have to be chosen and configured. The set of combinations of the given choices form a huge design space which is infeasible to test manually. Simulating the different deployment options assists to find the best ratio between high performance and low costs. For this purpose, we developed a simulation tool named CDOSim that can simulate those cloud deployment options. CDOSim integrates into the cloud migration framework CloudMIG Xpress and utilizes KDM models that were extracted by a reverse engineering process. Furthermore, it is possible to use monitored workload profiles as a simulation input. Our evaluation shows that CDOSim's simulation results can support software engineers to sufficiently accurate predict the cost and performance properties of software systems when deployed to private and real world public cloud environments such as Eucalyptus and Amazon EC2, respectively. Thus, CDOSim can be used for the simulation of cloud

Reseña del editor

Master's Thesis from the year 2012 in the subject Computer Science - Software, grade: 1,0, Christian-Albrechts-University of Kiel, language: English, abstract: Cloud computing is emerging as a promising new paradigm that aims at delivering computing resources and services on demand. To cope with the frequently found over- and under-provisioning of resources in conventional data centers, cloud computing technologies enable to rapidly scale up and down according to varying workload patterns. However, most software systems are not built for utilizing this so called elasticity and therefore must be adapted during the migration process into the cloud. A challenge during migration is the high number of different possibilities for the deployment to cloud computing resources. For example, there exist a plethora of potential cloud provider candidates. Here, the selection of a specific cloud provider is the most obvious and basic cloud deployment option. Furthermore, the mapping between services and virtual machine instances must be considered when migrating to the cloud and the specific adaptation strategies, like allocating a new virtual machine instance if the CPU utilization is above a given threshold, have to be chosen and configured. The set of combinations of the given choices form a huge design space which is infeasible to test manually. Simulating the different deployment options assists to find the best ratio between high performance and low costs. For this purpose, we developed a simulation tool named CDOSim that can simulate those cloud deployment options. CDOSim integrates into the cloud migration framework CloudMIG Xpress and utilizes KDM models that were extracted by a reverse engineering process. Furthermore, it is possible to use monitored workload profiles as a simulation input. Our evaluation shows that CDOSim's simulation results can support software engineers to sufficiently accurate predict the cost and performance properties of software systems when dep

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
diplom.de
Año de publicación
2014
Idioma
Inglés
ISBN 10 
3956366964
ISBN 13 
9783956366963
Encuadernación
Tapa blanda
Número de páginas
156
Contacto del fabricante
no disponible
Persona responsable
no disponible

Otras ediciones populares con el mismo título

9783954893935: Simulating Cloud Deployment Options for Software Migration Support

Edición Destacada

ISBN 10:  3954893932 ISBN 13:  9783954893935
Editorial: Anchor Academic Publishing, 2015
Tapa blanda