Simulating Cloud Deployment Options by Fittkau Florian (28 results)

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Taschenbuch. Condition: Neu. Simulating Cloud Deployment Options for Software Migration Support | Florian Fittkau | Taschenbuch | 156 S. | Englisch | 2014 | [.] | EAN 9783956366963 | Verantwortliche Person für die EU: Dryas Verlag, ein Imprint der Bedey und Thoms Media GmbH, Hermannstal 119k, 22119 Hamburg, kontakt[at]dryas[dot]de | Anbieter: preigu.

Taschenbuch. Condition: Neu. Simulating Cloud Deployment Options for Software Migration Support | Florian Fittkau | Taschenbuch | 160 S. | Englisch | 2015 | Anchor Academic Publishing | EAN 9783954893935 | Verantwortliche Person für die EU: Dryas Verlag, ein Imprint der Bedey und Thoms Media GmbH, Hermannstal 119k, 22119 Hamburg, kontakt[at]dryas[dot]de | Anbieter: preigu.

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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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.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.The simulation of a cloud deployment option can assist in solving this problem. A simulation is often faster than executing real world experiments. Furthermore, the adaptation to the software system that shall be migrated requires less effort at a modeling layer. The simulation can be utilized by an automatic optimization algorithm to find the best ratio between high performance and low costs.Our main objective in this study is the implementation of a software that enables the simulation of cloud deployment options on a language independent basis. 160 pp. Englisch.

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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 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 deployment options and assists to find the best suited cloud deployment option for existing software systems. 156 pp. Englisch.

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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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 resourc.

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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 technologie.

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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.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. The simulation of a cloud deployment option can assist in solving this problem. A simulation is often faster than executing real world experiments. Furthermore, the adaptation to the software system that shall be migrated requires less effort at a modeling layer. The simulation can be utilized by an automatic optimization algorithm to find the best ratio between high performance and low costs. Our main objective in this study is the implementation of a software that enables the simulation of cloud deployment options on a language independent basis.Books on Demand GmbH, Überseering 33, 22297 Hamburg 160 pp. Englisch.

Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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 deployment options and assists to find the best suited cloud deployment option for existing software systems.Diplomica Verlag, Hermannstal 119k, 22119 Hamburg 156 pp. Englisch.

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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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 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 deployment options and assists to find the best suited cloud deployment option for existing software systems.

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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.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.The simulation of a cloud deployment option can assist in solving this problem. A simulation is often faster than executing real world experiments. Furthermore, the adaptation to the software system that shall be migrated requires less effort at a modeling layer. The simulation can be utilized by an automatic optimization algorithm to find the best ratio between high performance and low costs.Our main objective in this study is the implementation of a software that enables the simulation of cloud deployment options on a language independent basis.

PAP. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.