Articoli correlati a Cloud Computing for Data-Intensive Applications
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This book presents a range of cloud computing platforms for data-intensive scientific applications. It covers systems that deliver infrastructure as a service, including: HPC as a service; virtual networks as a service; scalable and reliable storage; algorithms that manage vast cloud resources and applications runtime; and programming models that enable pragmatic programming and implementation toolkits for eScience applications. Many scientific applications in clouds are also introduced, such as bioinformatics, biology, weather forecasting and social networks. Most chapters include case studies.Cloud Computing for Data-Intensive Applications targets advanced-level students and researchers studying computer science and electrical engineering. Professionals working in cloud computing, networks, databases and more will also find this book useful as a reference.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Contenuti
Scalable Deployment of a LIGO Physics Application on Public Clouds:Workflow Engine and Resource Provisioning Techniques.- The FutureGrid Testbed for Big Data.- Cloud Networking to Support Data Intensive Applications.- IaaS cloud benchmarking: approaches, challenges, and experience.- Adaptive Workload Partitioning and Allocation for Data Intensive Scientific Applications.- Federating Advanced CyberInfrastructures with Autonomic Capabilities.- Executing Storm Surge Ensembles on PAAS Cloud.- Migrating Scientific Workflow Management Systems from the Grid to the Cloud.- Efficient Task-Resource Matchmaking Using Self-Adaptive Combinatorial Auction.- Cross-Phase Optimization in MapReduce.- DRAW: A New Data-gRouping-AWare Data Placement Scheme for Data Intensive Applications with Interest Locality.- Maiter: An Asynchronous Graph Processing Framework for Delta-based Accumulative Iterative Computation.- GPU-Accelerated Cloud Computing Data-Intensive Applications.- Big Data Storage and Processing on Azure Clouds: Experiments at Scale and Lessons Learned.- Storage and Data Lifecycle Management in Cloud Environments with FRIEDA.- DTaaS: Data Transfer as a Service in the Cloud.- Supporting a Social Media Observatory with Customizable Index Structures — Architecture and Performance.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
- EditoreSpringer-Nature New York Inc
- Data di pubblicazione2014
- ISBN 10 1493919040
- ISBN 13 9781493919048
- RilegaturaCopertina rigida
- LinguaInglese
- Numero di pagine436
- RedattoreLi Xiaolin, Qiu Judy
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. One of the first books on cloud computing for eScience and data-intensive applicationsIncludes a special focus on programming models in cloudsProvides detailed case studiesThis book presents a range of cloud computing platforms for data-in. Codice articolo 4214261
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Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents a range of cloud computing platforms for data-intensive scientific applications. It covers systems that deliver infrastructure as a service, including: HPC as a service; virtual networks as a service; scalable and reliable storage; algorithms that manage vast cloud resources and applications runtime; and programming models that enable pragmatic programming and implementation toolkits for eScience applications. Many scientific applications in clouds are also introduced, such as bioinformatics, biology, weather forecasting and social networks. Most chapters include case studies.Cloud Computing for Data-Intensive Applications targets advanced-level students and researchers studying computer science and electrical engineering. Professionals working in cloud computing, networks, databases and more will also find this book useful as a reference. Codice articolo 9781493919048
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