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Cloud computing for data-intensive applications /
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 a...
| Other Authors: | , |
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| Format: | Printed Book |
| Language: | English |
| Subjects: | |
| Online Access: | Publisher description Table of contents only |
Table of Contents:
- 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.