Read Microsoft Word - Distributed Computing-Front Matter-ToC-Jun5-2011.docm text version

Morgan Kaufman Publisher, an Imprint of Elsevier, announces the forthcoming publication of Distributed and Cloud Computing: Clusters, Grids, Clouds and The Future Internet by Kai Hwang, Geoffrey Fox and Jack Dongarra. The book will be available in Sept. 2011.

About The Co-authors :

Kai Hwang is a Professor of Electrical Engineering and Computer Science, University of Southern California.

Presently, he also serves as an Intellectual Venture-endowed Visiting Chair Professor at Tsinghua University in Beijing. He earned the Ph.D. in EECS from University of California at Berkeley in 1972. He has taught at Purdue University for 12 years prior to joining USC in 1985. Hwang has served as the founding Editor-in-Chief of the Journal of Parallel and Distributed Computing for 26 years. He is a world-renowned scholar and educator in computer science and engineering. He has published 8 books and 220 original papers in computer architecture, digital arithmetic, parallel processing, distributed systems, Internet security, and cloud computing. Four of his published books: Computer Arithmetic ( Wiley, 1978), Computer architecture and Parallel Processing (McGraw-Hill 1983), Advanced Computer Architecture (McGraw-Hill 1993), and Scalable Parallel Computing ( McGraw-Hill, 1998) have been translated into Spanish, Japanese, Chinese and Korean from the English editions. By 2011, his published work were cited with an h-index 40 (meaning 40 papers cited at least 40 times each) and a g-index of 92 (meaning 92 papers and books that were cited 92×92= 8,464 times collectively). Dr. Hwang has delivered 34 keynote addresses in major IEEE/ACM Conferences. In 1986, IEEE Computer Society elevated him an IEEE Fellow. He received the 2004 Outstanding Achievement Award from China Computer Federation. In May 2011,he received the 25-year IPDPS Founders' Award for his pioneering contributions in the field of parallel processing. Visit http:// GridSec.usc.edu/hwang.html for details.

Distributed and Cloud Computing

: Clusters, Grids, Clouds and The Future Internet

Kai Hwang, Geoffrey Fox, Jack Dongarra

About the Book:

Cloud-based distributed systems such as Google AppEngine, Amazon Web Service, Facebook, SalesForce.com and many others play an increasingly important role in upgrading the web services and Internet applications. Future computer architects, software engineers, and system designers need to understand the principles and underline technologies, in order to build the Internet of tomorrow. This book explains how to create high-performance clusters, scalable networks, automated data centers, and high-throughput systems, and how to program and use distributed systems and cloud resources in innovative applications, effectively and efficiently. Starting with an overview of modern distributed models, the text exposes the design principles, system architectures and innovative applications of parallel, distributed, and cloud computing systems. The book describes cloud-based or scalable systems for research, e-commerce, social networking, supercomputing, and more, using examples from open-source and commercial vendors. The book is primarily authored by three leading computer and IT scientists. They have also edited the partial contributions by 30 top researchers from the US, China, and Australia. Collectively, This group of authors and contributors consolidate the impressive progress that has taken place in parallel processing and distributed computing over the past 30 years, The book aims to transforme cluster and grid/P2P computing towards ubiquitous use of public and private clouds, Internet of things, and cyber-physical systems in the years to come.

Geoffrey Fox is a Professor of Informatics, Computing and Physics and Associate Dean of Graduate studies

and Research at the same College, 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 60+ Ph.D. students in computer science and engineering over the years. Contact him via : [email protected]

Jack Dongarra is a University Distinguished Professor of Electrical Engineering and Computer Science,

University of Tennessee and a Distinguished Research Staff, Oak Ridge National Lab. An ACM/IEEE/ SIAM/AAAS Fellow, Dongarra pioneered the areas of supercomputer benchmarks, numerical analysis, PDE 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. Contact him by [email protected]

List of Contributors: Various chapters, sections or examples in the book are partially contributed or

technically assisted by the following IT and computing experts and professionals from the USA, China and Australia, who have been working closely with the lead authors over the years. Albert Zomaya, Nikzad Rivandi, Young-Choon Lee, Ali Boloori, Reza Moraveji, Javid Taheri, and Chen Wang, Sydney University; Australia; Rajkumar Buyya, University of Melbourne; Australia Judy Qiu, Shrideep Pallickara, Marlon Pierce, Suresh Marru, Gregor von Laszewski, Javier Diaz, Archit Kulshrestha, and Andrew J. Younge, Indiana University; Yongwei Wu, Weimin Zheng, and Kang Chen, Tsinghua University; China; Zhenyu Li, Ninghui Sun, Zhiwei Xu, and , Gaogang Xie, Institute of Computing Technology, Chinese Academy of Sciences; Zhibin Yu, Xiaofei Liao and Hai Jin, Huazhong Univ. of Science and Technology; China Kaikun Dong, Zhongyuan Qin, Vikram Dixit, Xiaosong Lou, and Zhou Zhao, University of Southern California; Michael McLennan, George Adams III, and Gerhard Klimeck, Purdue University; Renato Figueiredo, University of Florida, and Michael Wilde, University of Chicago.

Key Features:

· Complete coverage of modern distributed computing technology including computer clusters, virtualization, service -oriented architecture, massively parallel processors, peer-to-peer networking, cloud computing and the Internet of things. Includes case studies from the leading distributed computing vendors: Amazon, Google, Microsoft, IBM, HP, Sun Microsystems, Silicon Graphics, and more. Major emphases of the book lie in exploiting the ubiquity, agility, efficiency, scalability, availability, and programmability of parallel and distributed computing systems. Over 100 examples are illustrated with 300 figures, designed to meet the need of students taking a distributed system course, each chapter include exercises and further reading Lecture slides, homework solutions, sample tests and topics for term projects and suggestions of extended research and benchmark projects will be made available to instructors, once the book is adopted for classroom use.

· · ·

Points of Contact and Web Site:

Kai Hwang, [email protected], University of Southern California, Todd Green, Morgan Kaufmann Publishers, [email protected] Publisher's Web site: http://mkp.com/category/news/coming-soon

·

Who Should Read This Book:

Students taking a distributed systems or distributed computing class. Professional system designers and engineers looking for a reference to the latest distributed technologies including clusters, grids, clouds and the Internet of Things. The book gives a balanced coverage of all of these topics, looking into the future of Internet and IT development.

Distributed and Cloud Computing: Clusters, Grids, Clouds and The Future Internet

All rights reserved by Morgan Kaufmann Publishers, May 4, 2011

1

Distributed and Cloud Computing: Clusters, Grids, Clouds and The Future Internet

All rights reserved by Morgan Kaufmann Publishers, May 4, 2011

2

Table of Contents: (Revised June 5, 2011)

Part 1: Systems Modeling, Clustering and Virtualization

Chapter 1: Distributed System Models and Enabling Technologies

1.1 Scalable Computing Service over The Internet

1.1.1 1.1.2 1.1.3 1.2.1 1.2.2 1.2.3 1.2.4 1.2.5 1.3.1 1.3.2 1.3.3 1.3.4 The Age of Internet Computing Computing Trends and New Paradigms Internet of Things and Cyber-Physical Systems Multicore, Many-Core and Multithreading Technologies GPU Computing To Exascale and Beyond Memory, Storage and System-Area Networking Virtual Machines and Virtualization Middleware Datacenter Virtualization for Cloud Computing Clusters of Cooperative Computers Grid Computing Infrastructures Peer-to-Peer Network Families Cloud Computing over The Internet

2.3.1 2.3.2 2.3.3 2.3.4

Single System Images Features High-Availability Through Redundancy Fault-Tolerant Cluster Configurations Checkpointing and Recovery Techniques

2.4

Cluster Job and Resource Management

2.4.1 2.4.2 2.4.3 2.4.4 Cluster Job Scheduling Methods Cluster Job Management Systems Load Sharing Facility (LSF) for Cluster Computing MOSIX ­ An OS for Linux Clusters and Clouds

2.5

Case Studies of Supercomputers and MPP Systems

2.5.1 2.5.2 2.5.3 Tianhe-1A: The World Fastest Supercomputer in 2010 Cray XT-5 Jaguar : The Top Supercomputer in 2009 IBM RoadRunner: The Top Supercomputer in 2008

1.2 Technologies for Network-based Computing

2.6 Bibliographic Notes and Homework Problems

Chapter 3: Virtual Machines and Virtualization of Clusters and Datacenters 3.1 Implementation Levels of Virtualization

3.1.1 3.1.2 3.1.3 3.1.4 Levels of Virtualization Implementation VMM Design Requirements and Providers Virtualization Support at the OS Level Middleware or Library Support for Virtualization

1.3 System Models for Distributed and Cloud Computing

1.4

Software Environments for Distributed Systems

1.4.1 1.4.2 1.4.3 Service-Oriented Architecture (SOA) Distributed Operating Systems and Software Tools Parallel/Distributed Programming Models

3.2

Virtualization Structures/Tools and Mechanisms

3.2.1 3.2.2 3.2.3 Hypervisor and XEN Architectures Binary Translation with Full Virtualization Para Virtualization with Compiler Support

1.5

Performance, Security, and Energy-Efficiency

1.5.1 1.5.2 1.5.3 1.5.4 Performance Metrics and System Scalability Fault-Tolerance and System Availability Network Threats and Data Integrity Energy-Efficiency in Distributed Computing

3.3

Virtualization of CPU, Memory and I/O Devices

3.3.1 3.3.2 3.3.3 3.3.4 3.3.5 Hardware Support for Virtualization CPU Virtualization Memory Virtualization I/O Virtualization Multi-core Virtualization

1.6

Bibliographic Notes and Homework Problems

3.4

Virtual Clusters and Resource Management

3.4.1 3.4.2 3.4.3 3.4.4 Physical versus Virtual Clusters Live VM Migration Steps and Performance Effects Migration of Memory, File and Network Resources Dynamic Deployment of Virtual Clusters

Chapter 2: Computer Clusters for Scalable Computing

2.1 Clustering for Massive Parallelism

2.1.1 2.1.2 2.1.3 2.1.4 Historical Cluster Development Trends Design Objectives of Computer Clusters Fundamental Cluster Design Issues Analysis of Top-500 Supercomputers

3.5

Virtualization for Datacenter Automation

3.5.1 3.5.2 3.5.3 3.5.4 Server Consolidation in Datacenters Virtual Storage Management Cloud OS for Virtualizing Datacenters Trust Management in Datacenter Design

2.2 Computer Clusters and MPP Architectures

2.2.1 2.2.2 2.2.3 2.2.4 2.2.5 Cluster Organization and Resource Sharing Node Architectures and MPP Packaging Cluster System Interconnects Hardware, Software, and Middleware Support GPU Clusters for Massive Parallelism

3.6

Bibliographic Notes and Homework Problems

2.3 Design Principles of Computer Clusters Distributed and Cloud Computing: Clusters, Grids, Clouds and The Future Internet

All rights reserved by Morgan Kaufmann Publishers, May 4, 2011

3

Distributed and Cloud Computing: Clusters, Grids, Clouds and The Future Internet All rights reserved by Morgan Kaufmann Publishers, May 4, 2011

4

Part 2: Computing Clouds and Service-Oriented Architecture

Chapter 4: Cloud Platform Architecture over Virtualized Data Centers

4.1 Cloud Computing and Service Models

4.1.1 4.1.2 4.1.3 4.1.4 Public, Private, and Hybrid Clouds Cloud Ecosystem and Enabling Technologies Infrastructure-as- a-Service (IaaS) Model Platform- and Software-as-a-Service (Paas, SaaS)

5.2.3 5.2.4 5.3.1 5.3.2 5.3.3

Queuing and Messaging Systems Illustrative Examples of Middleware Science Gateway Exemplars HUBzeroTM Platform for Scientific Collaboration Open Gateway Computing Environments OGCE UDDI and Service Registries Databases and Publish-Subscribe Metadata catalogues Semantic Web and Grid Job Execution Environments and Monitoring Basic Concepts of Workflow Workflow Standards Workflow Architecture and Specification Workflow Execution Engine Example of a Scripting Workflow System

5.3 Portals and Science Gateways

5.4

Discovery, Registries, Metadata, and Databases

5.4.1 5.4.2 5.4.3 5.4.4 5.4.5 5.5.1 5.5.2 5.5.3 5.5.4 5.5.5

4.2

Datacenter Design and Interconnection Networks 4.2.1 Warehouse-Scale Datacenter Design

4.2.2 4.2.3 7.2.4 7.2.5 4.3.1 4.3.2 4.3.3 4.3.4 Datacenter Interconnections Networks Modular Datacenter in Truck Container Interconnection of Modular datacenters Datacenter Management Issues A Generic Cloud Architecture Design Layered Cloud Architectural development Virtualization Support and Disaster Recovery Architectural Design Challenges Public Clouds and Service Offerings Google Application Engine (GAE) Amazon Web Service (AWS) Microsoft Windows Azure Extended Cloud Computing Services Resource Provisioning and Platform Deployment Virtual Machine Creation and Management Global Exchange of Cloud Resources Cloud Security Defense Strategies Distributed Intrusion/.Anomaly Detection Data and Software Protection Techniques Reputation-Guided Protection of Datacenters

5.5 Workflow in Service-Oriented Architectures

4.3 Architecture Design of Compute and Storage Clouds 5.6

Bibliographic Notes and Homework Problems

4.4

Public Cloud Platforms: GAE, AWS and Azure

4.4.1 4.4.2 4.4.3 4.4.4

Chapter 6: Cloud Programming and Software Environments

6.1 Features of Cloud and Grid Platforms

6.1.1 6.1.2 6.1.3 6.1.4 Cloud Capabilities and Platform Features Traditional Features Common To Grids and Clouds Data Features and Databases Programming and Runtime Features Parallel Computing and Programming Paradigms MapReduce, Twister and Iterative MapReduce Hadoop Library from Apache Dryad and DryadLINQ from Microsoft Sawzall and Pig Latin- High-Level Languages Mapping Applications to Parallel and Distributed Systems Programming the Google App Engine Google File System (GFS) Bigtable, Google's NOSQL system Chubby, Google's Distributed Lock service Programming on Amazon EC2 Amazon Simple Storage Service (S3) Amazon Elastic Block Store EBS and SimpleDB Microsoft Azure programming Support Open Source Eucalyptus and Nimbus OpenNebula, Sector/Sphere, and OpenStack Manjrasoft Aneka Cloud and Appliances

4.5 Inter-Cloud Cloud Resource Management

4.5.1

4.5.2 4.5.3 4.5.4

6.2

Parallel and Distributed Programming Paradigms

6.2.1 6.2.2 6.2.3 6.2.4 6.2.5 6.2.6

4.6

Cloud Security and Trust Management

4.6.1 4.6.2 4.6.3 4.6.4

6.3

Programming Support of Google App Engine

6.3.1 6.3.2 6.3.3 6.3.4

4.7

References and Homework Problems

6.4

Chapter 5: Service Oriented Architectures

5.1 Services and Service Oriented Architectures

5.1.1 5.1.2 5.1.3 5.1.4 5.1.5 REST and Systems of Systems Services and Web Services Enterprise Multi-tier Architecture Grid Services and OGSA Other Service Oriented Architectures and Systems Enterprise Bus Publish-Subscribe Model and Notification

Programming on Amazon AWS and Microsoft Azure

6.4.1 6.4.2 6.4.3 6.4.4

6.6

Emerging Cloud Software Environments

6.6.1 6.6.2 6.6.3

5.2

Message-Oriented Middleware

5.2.1 5.2.2

6.7

Bibliographic Notes and Homework Problems

Distributed and Cloud Computing: Clusters, Grids, Clouds and The Future Internet

All rights reserved by Morgan Kaufmann Publishers, May 4, 2011

5

Distributed and Cloud Computing: Clusters, Grids, Clouds and The Future Internet

All rights reserved by Morgan Kaufmann Publishers, May 4, 2011

6

Part 3: Grids, P2P, and The Future Internet

Chapter 7: Grid Computing and Resource Management

7.1 Grid Architecture and Service Modeling

7.1.1 7.1.2 7.1.3 7.1.4 Grid History and Service Evolution CPU Scavengging and Virtual Supercomputers Open Grid Services Architecture (OGSA) Data-Intensive Grid Service Models

8.4

Trust, Reputation and Security Management

8.4.1 8.4.2 8.4.3 8.4.4 Peer Trust and Reputation Systems Trust Overlay and DHT Implementation PowerTrust ­ A Scalable Reputation System Securing Overlays to Prevent Network Attacks

8.5

P2P File Sharing and Copyright Protection

8.5.1 8.5.2 8.5.3 8.5.4 Fast Search, Replica and Consistency P2P Content Delivery Networks Copyright Protection Issues and Solutions Collusive Piracy Prevention in P2P Networks

7.2

Case Studies of Grid Computing Systems

7.2.1 7.2.2 7.2.3 7.2.4 National and International Grid Projects The NSF TeraGrid in The USA The DataGrid built by European Union The ChinaGrid Design Experiences

8.6 Bibliographic Notes and Homework Problems

Chapter 9: Ubiquitous Clouds and The Internet of Things

9.1 Cloud Trends in Supporting Ubiquitous Computing

9.1.1 9.1.2 9.1.3 9.1.4 Use of Clouds for HPC/HTC and Ubiquitous Computing Large-Scale Private Clouds (NASA, CERN, etc.) Cloud Mashup for Agility and Scalability Cloudlets for Mobile Cloud Computing Review of Science and Research Clouds Data-Intensive Scalable Computing (DISC) Performance Metrics for HPC/HTC Systems Quality of Service of HTC Systems Benchmarking MPI, Azure, EC2, MapReduce, Hadoop The Internet of Things for Ubiquitous Computing Radio-Frequency Identification (RFID) Sensor Networks and Zigbee Technology Global Positioning Systems (GPS) Applications of The Internet of Things Retailing and Supply-Chain Management Smart Power Grid and Smart Buildings Cyber-Physical Systems (CPS) Online Social Network Characteristics Graph-Theoretic Analysis of Social networks Communities and Applications of Social Networks Facebook: The World's Largest Content-Sharing Network Twitter for Microblogging, News and Alert Services

7.3

Grid Resource Management and Brokering

7.3.1 7.3.2 7.3.3 7.3.4 Resource Management and Job Scheduling Grid Resource Monitoring ­ The CGSV Experiences Service Accounting and Economy Model Grid Resource Brokering ­The Gridbus Experiences

9.2

Performance of Distributed Systems and The Cloud

9.2.1 9.2.2 9.2.3 9.2.4 9.2.5

7.4

Middleware Support for Grid Computing

7.4.1 7.4.2 7.4.3 7.4.4 Open-Source Grid Middleware Packages The Globus Toolkit Architecture (GT4) Globus Containers and Resource/Data Management The ChinaGrid Support Platform (CGSP)

9.3

Enabling Technologies for The Internet of Things

9.3.1 9.3.2 9.3.3 9.3.4

7.5

Grid Application Trends and Security Measures

7.5.1 7.5.2 7.5.3 7.5.4 7.5.5 Grid Trends and Technology Fusion Grid Performance Prediction Trust Models for Grid security Authentication and Authorization Globus Security Infrastructure (GSI)

9.4

Innovative Applications of The Internet of Things

9.4.1 9.4.2 9.4.3 9.4.4

7.6

Bibliographic Notes and Homework Problems

Chapter 8: P2P Computing with Overlay Networks

8.1 Peer-to-Peer Computing Systems

8.1.1 8.1.2 8.1.3 Basic Concepts of P2P Computing Systems Fundamental Challenges in P2P Computing Taxonomy of P2P Network Systems

9.5

Social Networks and Innovative Applications

9.5.1 9.5.2 9.5.3 9.5.4 9.5.5

8.2 P2P Overlay Networks and Properties

8.2.1

8.2.2 8.2.3 8.2.4 Unstructured P2P Overlay Networks Distributed Hash Tables (DHT) Structured P2P Overlay Networks Hierarchically Structured P2P Overlay Networks

9.6

Bibliographic Notes and Homework Problems (To be compiled by MK Publisher)

Subject Index

8.3 Routing, Proximity and Fault Tolerance

8.3.1 8.3.2 8.3.3 8.3.4 Routing in P2P Overlay Networks Network Proximity in P2P Overlays Fault Tolerance and Failure Recovery Churn Resilience Against Failures

(Note to Morgan Kaufmann Production Team: In total, the final manuscript has 512 pages including 103 illustrated Examples, 312 Figures, 83 Tables, and 154 Homework Problems )

Distributed and Cloud Computing: Clusters, Grids, Clouds and The Future Internet

All rights reserved by Morgan Kaufmann Publishers, May 4, 2011

7

Distributed and Cloud Computing: Clusters, Grids, Clouds and The Future Internet

All rights reserved by Morgan Kaufmann Publishers, May 4, 2011

8

Information

Microsoft Word - Distributed Computing-Front Matter-ToC-Jun5-2011.docm

4 pages

Report File (DMCA)

Our content is added by our users. We aim to remove reported files within 1 working day. Please use this link to notify us:

Report this file as copyright or inappropriate

74988


Notice: fwrite(): send of 208 bytes failed with errno=104 Connection reset by peer in /home/readbag.com/web/sphinxapi.php on line 531