Speeding-up codon analysis on the cloud with local MapReduce aggregation
Information Sciences: an International Journal
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Mastering Cloud Computing is designed for undergraduate students learning to develop cloud computing applications. Tomorrow's applications won't live on a single computer but will be deployed from and reside on a virtual server, accessible anywhere, any time. Tomorrow's application developers need to understand the requirements of building apps for these virtual systems, including concurrent programming, high-performance computing, and data-intensive systems. The book introduces the principles of distributed and parallel computing underlying cloud architectures and specifically focuses on virtualization, thread programming, task programming, and map-reduce programming. There are examples demonstrating all of these and more, with exercises and labs throughout.Explains how to make design choices and tradeoffs to consider when building applications to run in a virtual cloud environmentReal-world case studies include scientific, business, and energy-efficiency considerationsTable of Contents1. Introduction 2. Principles of Parallel and Distributed Computing 3. Virtualization 4. Cloud Computing Architecture 5. Aneka: Cloud application platform 6. Concurrent Computing: Thread programming 7. High-Throughput Computing: Task Programming 8. Data Intensive Computing: Map-Reduce Programming 9. Cloud Platforms in Industry 10. Cloud Applications 11. Advanced Topics in Cloud Computing