Cloud Computing〈2nd ed. 2017〉 : Principles, Systems and Applications(2)

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¥43,715
  • 電子書籍
  • ポイントキャンペーン

Cloud Computing〈2nd ed. 2017〉 : Principles, Systems and Applications(2)

  • 著者名:Antonopoulos, Nick (EDT)/Gillam, Lee (EDT)
  • 価格 ¥34,405 (本体¥31,278)
  • Springer(2017/06/02発売)
  • 春分の日の三連休!Kinoppy 電子書籍・電子洋書 全点ポイント30倍キャンペーン(~3/22)
  • ポイント 9,360pt (実際に付与されるポイントはご注文内容確認画面でご確認下さい)
  • 言語:ENG
  • ISBN:9783319546445
  • eISBN:9783319546452

ファイル: /

Description

This practically-focused reference presents a comprehensive overview of the state of the art in Cloud Computing, and examines the potential for future Cloud and Cloud-related technologies to address specific industrial and research challenges. This new edition explores both established and emergent principles, techniques, protocols and algorithms involved with the design, development, and management of Cloud-based systems. The text reviews a range of applications and methods for linking Clouds, undertaking data management and scientific data analysis, and addressing requirements both of data analysis and of management of large scale and complex systems. This new edition also extends into the emergent next generation of mobile telecommunications, relating network function virtualization and mobile edge Cloud Computing, as supports Smart Grids and Smart Cities. As with the first edition, emphasis is placed on the four quality-of-service cornerstones of efficiency, scalability, robustness, and security.

Table of Contents

Part I: General Principles.- The Rise of Cloud Computing in the Era of Emerging Networked Society.- Mirror, Mirror on the Wall, How Do I Dimension My Cloud After All?.- A Taxonomy of Adaptive Resource Management Mechanisms in Virtual Machines: Recent Progress and Challenges.- Part II: Science Cloud.- Exploring Cloud Elasticity in Scientific Applications.- Clouds and Reproducibility: A Way to Go to Scientific Experiments?.- Big Data Analytics in Healthcare: A Cloud-Based Framework for Generating Insights.- Part III: Data Cloud.- Implementing MapReduce Applications in Dynamic Cloud Environments.- High Performance Graph Data Management and Mining in Cloud Environments with X10.- Part IV: Multi-Clouds.- Facilitating Cloud Federation Management via Data Interoperability.- Applying Self-* Principles in Heterogeneous Cloud Environments.- Part V: Performance and Efficiency.- Optimizing the Profit and QoS of Virtual Brokers in the Cloud.- Adaptive Resource Allocation for Load Balancing in Cloud.- Cloud-Supported Certification for Energy-Efficient Web Browsing and Services.- Datacentre Event Analysis for Knowledge Discovery in Large-Scale Cloud Environments.

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