Cloud Computing for Data-Intensive Applications

✍ Scribed by Xiaolin Li, Judy Qiu (eds.)

Publisher: Springer-Verlag New York
Year: 2014
Tongue: English
Leaves: 425
Edition: 1
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

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.

✦ Table of Contents

Front Matter....Pages i-viii
Front Matter....Pages 1-1
Scalable Deployment of a LIGO Physics Application on Public Clouds: Workflow Engine and Resource Provisioning Techniques....Pages 3-25
The FutureGrid Testbed for Big Data....Pages 27-59
Cloud Networking to Support Data Intensive Applications....Pages 61-81
IaaS Cloud Benchmarking: Approaches, Challenges, and Experience....Pages 83-104
GPU-Accelerated Cloud Computing for Data-Intensive Applications....Pages 105-129
Adaptive Workload Partitioning and Allocation for Data Intensive Scientific Applications....Pages 131-148
DRAW: A New Data-gRouping-AWare Data Placement Scheme for Data Intensive Applications with Interest Locality....Pages 149-174
Front Matter....Pages 175-175
Efficient Task-Resource Matchmaking Using Self-adaptive Combinatorial Auction....Pages 177-200
Federating Advanced Cyberinfrastructures with Autonomic Capabilities....Pages 201-227
Front Matter....Pages 229-229
Migrating Scientific Workflow Management Systems from the Grid to the Cloud....Pages 231-256
Executing Storm Surge Ensembles on PAAS Cloud....Pages 257-276
Cross-Phase Optimization in MapReduce....Pages 277-302
Asynchronous Computation Model for Large-Scale Iterative Computations....Pages 303-328
Front Matter....Pages 329-329
Big Data Storage and Processing on Azure Clouds: Experiments at Scale and Lessons Learned....Pages 331-355
Storage and Data Life Cycle Management in Cloud Environments with FRIEDA....Pages 357-378
Managed File Transfer as a Cloud Service....Pages 379-399
Supporting a Social Media Observatory with Customizable Index Structures: Architecture and Performance....Pages 401-427

✦ Subjects

Information Systems and Communication Service; Computer Communication Networks; Information Systems Applications (incl. Internet); Database Management

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