Book 2014

Cloud Computing for Data-Intensive Applications

Editors:

ISBN: 978-1-4939-1904-8 (Print) 978-1-4939-1905-5 (Online)

Table of contents (17 chapters)

  1. Front Matter

    Pages i-viii

  2. Systems and Applications

    1. Front Matter

      Pages 1-1

    2. No Access

      Chapter

      Pages 3-25

      Scalable Deployment of a LIGO Physics Application on Public Clouds: Workflow Engine and Resource Provisioning Techniques

    3. No Access

      Chapter

      Pages 27-59

      The FutureGrid Testbed for Big Data

    4. No Access

      Chapter

      Pages 61-81

      Cloud Networking to Support Data Intensive Applications

    5. No Access

      Chapter

      Pages 83-104

      IaaS Cloud Benchmarking: Approaches, Challenges, and Experience

    6. No Access

      Chapter

      Pages 105-129

      GPU-Accelerated Cloud Computing for Data-Intensive Applications

    7. No Access

      Chapter

      Pages 131-148

      Adaptive Workload Partitioning and Allocation for Data Intensive Scientific Applications

    8. No Access

      Chapter

      Pages 149-174

      DRAW: A New Data-gRouping-AWare Data Placement Scheme for Data Intensive Applications with Interest Locality

  3. Resource Management

    1. Front Matter

      Pages 175-175

    2. No Access

      Chapter

      Pages 177-200

      Efficient Task-Resource Matchmaking Using Self-adaptive Combinatorial Auction

    3. No Access

      Chapter

      Pages 201-227

      Federating Advanced Cyberinfrastructures with Autonomic Capabilities

  4. Programming Models

    1. Front Matter

      Pages 229-229

    2. No Access

      Chapter

      Pages 231-256

      Migrating Scientific Workflow Management Systems from the Grid to the Cloud

    3. No Access

      Chapter

      Pages 257-276

      Executing Storm Surge Ensembles on PAAS Cloud

    4. No Access

      Chapter

      Pages 277-302

      Cross-Phase Optimization in MapReduce

    5. No Access

      Chapter

      Pages 303-328

      Asynchronous Computation Model for Large-Scale Iterative Computations

  5. Cloud Storage

    1. Front Matter

      Pages 329-329

    2. No Access

      Chapter

      Pages 331-355

      Big Data Storage and Processing on Azure Clouds: Experiments at Scale and Lessons Learned

    3. No Access

      Chapter

      Pages 357-378

      Storage and Data Life Cycle Management in Cloud Environments with FRIEDA

    4. No Access

      Chapter

      Pages 379-399

      Managed File Transfer as a Cloud Service

    5. No Access

      Chapter

      Pages 401-427

      Supporting a Social Media Observatory with Customizable Index Structures: Architecture and Performance