Kai Hwang is a Professor of Computer Engineering, University of Southern California and an IV-endowed visiting Chair Professor, Tsinghua University, China. He earned the Ph.D. in EECS from University of California at Berkeley. An IEEE Life Fellow, He has published extensively in computer architecture, digital arithmetic, parallel processing, distributed systems, Internet security, and cloud computing. He has founded the Journal of Parallel and Distributed Computing and delivered three dozens of keynote addresses in major IEEE/ACM Conferences. He received the 2004 Outstanding Achievement Award from China Computer Federation and the IEEE 2011 IPDPS Founders' Award for his pioneering contributions in the field of parallel processing. Jack Dongarra is a University Distinguished Professor of Electrical Engineering and Computer Science, University of Tennessee, a Distinguished Research Staff, Oak Ridge National Laboratory and a Turning Fellow at the University of Manchester. An ACM/IEEE/ SIAM/AAAS Fellow, Dongarra pioneered the areas of supercomputer benchmarks, numerical analysis, linear algebra solvers, and high-performance computing and published extensively in these areas. He leads the Linpack benchmark evaluation of the Top-500 fastest computers over the years. Based on his high contributions in the supercomputing and high-performance areas, he was elected as a Member of the National Academy of Engineering in the USA. Geoffrey Fox is a Distinguished Professor of Informatics, Computing and Physics and Associate Dean of Graduate studies and Research in the School of Informatics and Computing, Indiana University. He has taught and led many research groups at Caltech and Syracuse University, previously. He received his Ph.D. from Cambridge University, U.K. Fox is well known for his comprehensive work and extensive publications in parallel architecture, distributed programming, grid computing, web services, and Internet applications. His book on Grid Computing (coauthored with F. Berman and Tony Hey) is widely used by the research community. He has produced over 60 Ph.D. students in physics, computer science and engineering over the years.

"Grid computing, peer-to-peer computing, cloud computing are emergent fields that have attracted academia and industry over the last few years. It is expected that they will have a huge impact on many areas in business, science and engineering and society at large. The timely publication of this textbook will bring the newest technologies in distributed computing to students." – Yi Pan, Dept of Computer Science, Georgia State University"Distributed and Cloud Computing is a comprehensive and up-to-date textbook that covers the convergence of high performance computing, distributed and cloud computing, virtualization, and grid computing. The authors integrate an awareness of application and technology trends that are shaping the future of computing. The book is an excellent resource for students as well as seasoned practitioners." –Thomas J. Hacker, Associate Professor, Purdue University"It is very well organized in nine chapters that allow readers interested in certain subtopics such as design, theory, service-oriented architecture, and resource management to find that material cohesively collected into a chapter that serves those interests. A valuable resource for students and practitioners of distributed and cloud computing. Summing Up: Highly recommended. Upper- division undergraduates, graduate students, professionals/practitioners, and general readers."--CHOICE

• Part 1: Systems Modeling, Clustering and Virtualization Chapter 1: Distributed System Models and Enabling Technologies1.1 Scalable Computing Service over The Internet 1.2 Technologies for Network-based Computing1.3 System Models for Distributed and Cloud Computing 1.4 Software Environments for Distributed Systems and Clouds 1.5 Performance, Security, and Energy-Efficiency 1.6 Bibliographic Notes and Homework Problems Chapter 2: Computer Clusters for Scalable Computing2.1 Clustering for Massive Parallelism 2.2 Computer Clusters and MPP Architectures 2.3 Design Principles of Computer Clusters 2.4 Cluster Job and Resource Management 2.5 Case Studies of Supercomputyers and MPP Systems 2.6 Bibliographic Notes and Homework Problems Chapter 3: Virtual Machines and Virtualization of Clusters and Datacenters 3.1 Implementation Levels of Virtualization 3.2 Virtualization Structures/Tools and Mechanisms 3.3 Virtualization of CPU, Memory and I/O Devices 3.4 Virtual Clusters and Resource Management 3.5 Virtualization for Datacenter Automation 3.6 Bibliographic Notes and Homework Problems Part 2: Computing Clouds and Service-Oriented ArchitectureChapter 4: Design of Cloud Computing Platforms4.1 Cloud Computing and Service Models 4.2 Datacenter Design and Interconnection Networks 4.3 Architecture Design of Compute and Storage Clouds 4.4 Public Cloud Platforms: GAE, AWS and Windows Azure 4.5 Cloud Resource Management and Exchanges 4.6 Cloud Security and Trust Management 4.7 References and Homework Problems Chapter 5: Service Oriented Architectures 5.1 Services and Service Oriented Architectures 5.2 Message-Oriented Middleware5.3 Portals and Science Gateways 5.4 Discovery, Registries, Metadata, and Databases 5.5 Workflow in Service-Oriented Architectures 5.6 Bibliographic Notes and Homework Problems Chapter 6: Cloud Programming and Software Environments6.1 Features of Cloud and Grid Platforms 6.2 Parallel and Distributed Programming Paradigms 6.3 Programming Support of Google App Engine 6.4 Amazon Web Services (AWS) Programming 6.5 Microsoft Azure Programming Support 6.6 Emerging Cloud Software Environments 6.7 Bibliographic Notes and Homework Problems Part 3: Grids, P2P, and The Future Internet Chapter 7: Grid Computing and Resource Management 7.1 Grid Architecture and Service Modeling 7.2 Case Studies of Grid Computing Systems 7.3 Grid Resource Management and Brokering 7.4 Middleware Support for Grid Resource Management 7.5 Grid Security Infrastructure in GT4 7.6 Bibliographic Notes and Homework Problems Chapter 8: P2P Computing with Overlay Networks 8.1 Peer-to-Peer Computing Systems 8.2 P2P Overlay Networks and Properties 8.3 Routing, Proximity and Fault Tolerance 8.4 Trust and Reputation Management 8.5 P2P File Sharing and Copyright Protection 8.6 Bibliographic Notes and Homework Problems Chapter 9: Ubiquitous Computing with Clouds and The Internet of Things9.1 Cloud Trend To Support Ubiquitous Computing 9.2 Performance Metrics for HPC and HTC Systems 9.3 Enabling Technologies for The Internet of Things 9.4 Innovative Applications of The Internet of Things 9.5 On-Line Social and Professional Networking 9.6 Bibliographic Notes and Homework Problems

Kai Hwang is a Professor of Computer Engineering, University of Southern California and an IV-endowed visiting Chair Professor, Tsinghua University, China. He earned the Ph.D. in EECS from University of California at Berkeley. An IEEE Life Fellow, He has published extensively in computer architecture, digital arithmetic, parallel processing, distributed systems, Internet security, and cloud computing. He has founded the Journal of Parallel and Distributed Computing and delivered three dozens of keynote addresses in major IEEE/ACM Conferences. He received the 2004 Outstanding Achievement Award from China Computer Federation and the IEEE 2011 IPDPS Founders' Award for his pioneering contributions in the field of parallel processing. Jack Dongarra is a University Distinguished Professor of Electrical Engineering and Computer Science, University of Tennessee, a Distinguished Research Staff, Oak Ridge National Laboratory and a Turning Fellow at the University of Manchester. An ACM/IEEE/ SIAM/AAAS Fellow, Dongarra pioneered the areas of supercomputer benchmarks, numerical analysis, linear algebra solvers, and high-performance computing and published extensively in these areas. He leads the Linpack benchmark evaluation of the Top-500 fastest computers over the years. Based on his high contributions in the supercomputing and high-performance areas, he was elected as a Member of the National Academy of Engineering in the USA. Geoffrey Fox is a Distinguished Professor of Informatics, Computing and Physics and Associate Dean of Graduate studies and Research in the School of Informatics and Computing, Indiana University. He has taught and led many research groups at Caltech and Syracuse University, previously. He received his Ph.D. from Cambridge University, U.K. Fox is well known for his comprehensive work and extensive publications in parallel architecture, distributed programming, grid computing, web services, and Internet applications. His book on Grid Computing (coauthored with F. Berman and Tony Hey) is widely used by the research community. He has produced over 60 Ph.D. students in physics, computer science and engineering over the years.

"Grid computing, peer-to-peer computing, cloud computing are emergent fields that have attracted academia and industry over the last few years. It is expected that they will have a huge impact on many areas in business, science and engineering and society at large. The timely publication of this textbook will bring the newest technologies in distributed computing to students." – Yi Pan, Dept of Computer Science, Georgia State University"Distributed and Cloud Computing is a comprehensive and up-to-date textbook that covers the convergence of high performance computing, distributed and cloud computing, virtualization, and grid computing. The authors integrate an awareness of application and technology trends that are shaping the future of computing. The book is an excellent resource for students as well as seasoned practitioners." –Thomas J. Hacker, Associate Professor, Purdue University"It is very well organized in nine chapters that allow readers interested in certain subtopics such as design, theory, service-oriented architecture, and resource management to find that material cohesively collected into a chapter that serves those interests. A valuable resource for students and practitioners of distributed and cloud computing. Summing Up: Highly recommended. Upper- division undergraduates, graduate students, professionals/practitioners, and general readers."--CHOICE

• Part 1: Systems Modeling, Clustering and Virtualization Chapter 1: Distributed System Models and Enabling Technologies1.1 Scalable Computing Service over The Internet 1.2 Technologies for Network-based Computing1.3 System Models for Distributed and Cloud Computing 1.4 Software Environments for Distributed Systems and Clouds 1.5 Performance, Security, and Energy-Efficiency 1.6 Bibliographic Notes and Homework Problems Chapter 2: Computer Clusters for Scalable Computing2.1 Clustering for Massive Parallelism 2.2 Computer Clusters and MPP Architectures 2.3 Design Principles of Computer Clusters 2.4 Cluster Job and Resource Management 2.5 Case Studies of Supercomputyers and MPP Systems 2.6 Bibliographic Notes and Homework Problems Chapter 3: Virtual Machines and Virtualization of Clusters and Datacenters 3.1 Implementation Levels of Virtualization 3.2 Virtualization Structures/Tools and Mechanisms 3.3 Virtualization of CPU, Memory and I/O Devices 3.4 Virtual Clusters and Resource Management 3.5 Virtualization for Datacenter Automation 3.6 Bibliographic Notes and Homework Problems Part 2: Computing Clouds and Service-Oriented ArchitectureChapter 4: Design of Cloud Computing Platforms4.1 Cloud Computing and Service Models 4.2 Datacenter Design and Interconnection Networks 4.3 Architecture Design of Compute and Storage Clouds 4.4 Public Cloud Platforms: GAE, AWS and Windows Azure 4.5 Cloud Resource Management and Exchanges 4.6 Cloud Security and Trust Management 4.7 References and Homework Problems Chapter 5: Service Oriented Architectures 5.1 Services and Service Oriented Architectures 5.2 Message-Oriented Middleware5.3 Portals and Science Gateways 5.4 Discovery, Registries, Metadata, and Databases 5.5 Workflow in Service-Oriented Architectures 5.6 Bibliographic Notes and Homework Problems Chapter 6: Cloud Programming and Software Environments6.1 Features of Cloud and Grid Platforms 6.2 Parallel and Distributed Programming Paradigms 6.3 Programming Support of Google App Engine 6.4 Amazon Web Services (AWS) Programming 6.5 Microsoft Azure Programming Support 6.6 Emerging Cloud Software Environments 6.7 Bibliographic Notes and Homework Problems Part 3: Grids, P2P, and The Future Internet Chapter 7: Grid Computing and Resource Management 7.1 Grid Architecture and Service Modeling 7.2 Case Studies of Grid Computing Systems 7.3 Grid Resource Management and Brokering 7.4 Middleware Support for Grid Resource Management 7.5 Grid Security Infrastructure in GT4 7.6 Bibliographic Notes and Homework Problems Chapter 8: P2P Computing with Overlay Networks 8.1 Peer-to-Peer Computing Systems 8.2 P2P Overlay Networks and Properties 8.3 Routing, Proximity and Fault Tolerance 8.4 Trust and Reputation Management 8.5 P2P File Sharing and Copyright Protection 8.6 Bibliographic Notes and Homework Problems Chapter 9: Ubiquitous Computing with Clouds and The Internet of Things9.1 Cloud Trend To Support Ubiquitous Computing 9.2 Performance Metrics for HPC and HTC Systems 9.3 Enabling Technologies for The Internet of Things 9.4 Innovative Applications of The Internet of Things 9.5 On-Line Social and Professional Networking 9.6 Bibliographic Notes and Homework Problems