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…mehr
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 environment Real-world case studies include scientific, business, and energy-efficiency considerations
Dr. Rajkumar Buyya is Redmond Barry Distinguished Professor and Director of the Cloud Computing and Distributed Systems (CLOUDS) Laboratory at the University of Melbourne, Australia. He is also serving as the founding CEO of Manjrasoft, a spin-off company of the University, commercializing its innovations in Cloud Computing. He has authored over 650 publications and seven textbooks including Mastering Cloud Computing from McGraw Hill, China Machine Press, and Morgan Kaufmann for Indian, Chinese and international markets respectively. Dr. Buyya is one of the most highly-cited authors in Computer Sience and Software Engineering worldwide. "A Scientometric Analysis of Cloud Computing Literature? by German scientists ranked Dr. Buyya as the World's Top-Cited Author and the World's Most-Productive Author in Cloud Computing. He has been recognized as a Web of Science "Highly Cited Researcher? for four consecutive years since 2016. Dr. Buyya was recognized as Scopus Researcher of the Year 2017 with Excellence in Innovative Research Award from Elsevier; "Lifetime Achievement Awards" from two Indian universities, and the "Best of the World,? in the Computing Systems field, by The Australian 2019 Research Review. Software technologies for Grid, Cloud, and Fog computing developed under Dr. Buyya's leadership have gained rapid acceptance and are in use at several academic institutions and commercial enterprises in 40 countries around the world. Dr. Buyya has led the establishment and development of key community activities, including serving as foundation Chair of the IEEE Technical Committee on Scalable Computing and five IEEE/ACM conferences. These contributions and the international research leadership of Dr. Buyya are recognized through the award of the "2009 IEEE Medal for Excellence in Scalable Computing? from the IEEE Computer Society TCSC. Manjrasoft's Aneka Cloud technology developed under his leadership has received the "Frost & Sullivan New Product Innovation Award." Dr. Buyya served as founding Editor-in-Chief of the IEEE Transactions on Cloud Computing. He is currently serving as Editor-in-Chief of Software: Practice and Experience, a long-standing journal in the field, established more than 50 years ago.
Inhaltsangabe
1. 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
