Cloud Computing for Data-Intensive Applications

1. Front Matter

   Pages i-viii

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2. Systems and Applications

   1. Front Matter

      Pages 1-1

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

      • Suraj Pandey, Letizia Sammut, Rodrigo N. Calheiros, Andrew Melatos, Rajkumar Buyya

      Pages 3-25

   3. The FutureGrid Testbed for Big Data

      • Gregor von Laszewski, Geoffrey C. Fox

      Pages 27-59

   4. Cloud Networking to Support Data Intensive Applications

      • Maurício Tsugawa, Andréa Matsunaga, José A. B. Fortes

      Pages 61-81

   5. IaaS Cloud Benchmarking: Approaches, Challenges, and Experience

      • Alexandru Iosup, Radu Prodan, Dick Epema

      Pages 83-104

   6. GPU-Accelerated Cloud Computing for Data-Intensive Applications

      • Baoxue Zhao, Jianlong Zhong, Bingsheng He, Qiong Luo, Wenbin Fang, Naga K. Govindaraju

      Pages 105-129

   7. Adaptive Workload Partitioning and Allocation for Data Intensive Scientific Applications

      • Xin Yang, Xiaolin Li

      Pages 131-148

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

      • Jun Wang, Pengju Shang, Jiangling Yin

      Pages 149-174

3. Resource Management

   1. Front Matter

      Pages 175-175

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   2. Efficient Task-Resource Matchmaking Using Self-adaptive Combinatorial Auction

      • Han Zhao, Xiaolin Li

      Pages 177-200

   3. Federating Advanced Cyberinfrastructures with Autonomic Capabilities

      • Javier Diaz-Montes, Ivan Rodero, Mengsong Zou, Manish Parashar

      Pages 201-227

4. Programming Models

   1. Front Matter

      Pages 229-229

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   2. Migrating Scientific Workflow Management Systems from the Grid to the Cloud

      • Yong Zhao, Youfu Li, Ioan Raicu, Cui Lin, Wenhong Tian, Ruini Xue

      Pages 231-256

   3. Executing Storm Surge Ensembles on PAAS Cloud

      • Abhirup Chakraborty, Milinda Pathirage, Isuru Suriarachchi, Kavitha Chandrasekar, Craig Mattocks, Beth Plale

      Pages 257-276

   4. Cross-Phase Optimization in MapReduce

      • Benjamin Heintz, Abhishek Chandra, Jon Weissman

      Pages 277-302

   5. Asynchronous Computation Model for Large-Scale Iterative Computations

      • Yanfeng Zhang, Qixin Gao, Lixin Gao, Cuirong Wang

      Pages 303-328

5. Cloud Storage

   1. Front Matter

      Pages 329-329

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

      • Radu Tudoran, Alexandru Costan, Gabriel Antoniu, Brasche Goetz

      Pages 331-355

   3. Storage and Data Life Cycle Management in Cloud Environments with FRIEDA

      • Lavanya Ramakrishnan, Devarshi Ghoshal, Valerie Hendrix, Eugen Feller, Pradeep Mantha, Christine Morin

      Pages 357-378

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.

• Benchmarking
• Big Data
• Cloud Computing
• Cloud Networking
• Cloud Services
• Cloud Storage
• Cyberinfrastructure
• Data Storage
• Data-intensive Computing
• Large-scale Computing
• Optimization
• Programming Models
• Social Media
• Workload Partitioning
• eScience

• University of Florida, Gainesville, USA

  Xiaolin Li

• Indiana University, Bloomington, USA

  Judy Qiu

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