Cloud Computing (eBook, PDF)

Principles, Systems and Applications

• Format: PDF

Produktbeschreibung

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.

Produktdetails

• Verlag: Springer International Publishing
• Erscheinungstermin: 2. Juni 2017
• Englisch
• ISBN-13: 9783319546452
• Artikelnr.: 53064386

Autorenporträt

Prof. Nick Antonopoulos is Dean of the College of Engineering and Technology, and Head of Research Excellence at the University of Derby, UK.

Dr. Lee Gillam is Editor-in-Chief of the Journal of Cloud Computing, and Director of Learning and Teaching and Senior Lecturer in the Department of Computer Science at the University of Surrey, UK.

Inhaltsangabe

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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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.