云计算与分布式系统

出版时间：2012-5  出版社：机械工业出版社  作者：(美）Kai Hwang,(美）Geoffrey C. Fox,(美）Jack J. Dongarra  页数：648  
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内容概要

　　随着信息技术的广泛应用和快速发展，云计算作为一种新兴的商业计算模型日益受到人们的广泛关注。本书是一本完整讲述云计算与分布式系统基本理论及其应用的教材。书中从现代分布式模型概述开始，介绍了并行、分布式与云计算系统的设计原理、系统体系结构和创新应用，并通过开源应用和商业应用例子，阐述了如何为科研、电子商务、社会网络和超级计算等创建高性能、可扩展的、可靠的系统。　　
　　《云计算与分布式系统：从并行处理到物联网（英文版）》特色：
　　全面覆盖现代分布式计算技术，包括集群、网格、面向服务的体系结构、大规模并行处理器、对等网络和云计算。
　　提供的案例研究来自主流分布式计算供应商，如亚马逊、微软、谷歌等。
　　解释如何利用虚拟化来促进管理、调试、迁移和灾难恢复。
　　专为本科生或研究生的分布式系统课程而设计——每章后都配有习题和进一步阅读建议，并为教师提供配套的PPT等教辅资源。

作者简介

　　Kai
Hwang（黄铠）美国南加州大学电子工程与计算机科学教授，互联网/云计算研究实验室主任；清华大学IV客座讲席教授；IEEE终身会士。他拥有加州大学伯克利分校
EECS博士学位，主要研究领域为云计算、分布式系统、高性能计算、普适计算、信任网格计算等。
现已发表论文220多篇，出版8本计算机体系结构、数字运算、并行处理、分布式系统、互联网安全和云计算方面的相关著作。他还创建了《the
Journal of Parallel and Distributed
Computing》，并获得了中国计算机学会2004杰出成就奖、IEEE2011 IPDPS创立者奖。
　　Geoffrey Fox
美国印第安那大学计算机科学、信息与物理学杰出教授，社会网格实验室主任。之前曾在加州理工和锡拉丘兹大学任教，并领导多个研究组。他拥有英国剑桥大学的
博士学位。Fox在并行体系结构、分布式编程、网格计算、Web服务和互联网应用方面做了广泛的工作并发表了大量作品。
　　Jack Dongarra 美国田纳西大学电子工程与计算机科学杰出教授，橡树岭国家实验室杰出研究员，曼彻斯特大学Turning
Fellow。他是ACM/IEEE/SIAM/AAAS
会士，是超级计算机基准测试、数值分析、线性代数解算器和高性能计算领域的先驱。多年以来，他都在负责Top
500最快计算机的Linpack基准测试评估。基于他在超级计算和高性能领域的巨大贡献，他被评为美国国家工程院院士。

书籍目录

Preface
About the Authors.
PART SYSTEMS MODELING, CLUSTERING
AND VIRTUALIZATION
CHAPTER Distributed System Models and Enabling Technologies
Summary
1.1 Scalable Computing over the Internet
1.1.1 The Age of Internet Computing
1.1.2 Scalable Computing Trends and New Paradigms8
1.1.3 The Internet of Things and Cyber-Physical Systems
1.2 Technologies for Network-Based Systems.13
1.2.1 Multicore CPUs and Multithreading Technologies
1.2.2 GPU Computing to Exascale and Beyond.
1.2.3 Memory, Storage, and Wide-Area Networking.
1.2.4 Virtual Machines and Virtualization Middleware.
1.2.5 Data Center Virtualization for Cloud Computing.
1.3 System Models for Distributed and Cloud Computing.
1.3.1 Clusters of Cooperative Computers.
1.3.2 Grid Computing Infrastructures.
1.3.3 Peer-to-Peer Network Families
1.3.4 Cloud Computing over the Internet.
1.4 Software Environments for Distributed Systems and Clouds.
1.4.1 Service-Oriented Architecture (SOA)
1.4.2 Trends toward Distributed Operating Systems.
1.4.3 Parallel and Distributed Programming Models.
1.5 Performance, Security, and Energy Efficiency
1.5.1 Performance Metrics and Scalability Analysis.
1.5.2 Fault Tolerance and System Availability.
1.5.3 Network Threats and Data Integrity
1.5.4 Energy Efficiency in Distributed Computing.
1.6 Bibliographic Notes and Homework Problems.
Acknowledgments.
References
Homework Problems.
Foreword.
CHAPTER Computer Clusters for Scalable Parallel Computing
Summary.
2.1 Clustering for Massive Parallelism
2.1.1 Cluster Development Trends
2.1.2 Design Objectives of Computer Clusters.
2.1.3 Fundamental Cluster Design Issues.
2.1.4 Analysis of the Top Supercomputers.
2.2 Computer Clusters and MPP Architectures
2.2.1 Cluster Organization and Resource Sharing
2.2.2 Node Architectures and MPP Packaging.
2.2.3 Cluster System Interconnects
2.2.4 Hardware, Software, and Middleware Support.
2.2.5 GPU Clusters for Massive Parallelism
2.3 Design Principles of Computer Clusters
2.3.1 Single-System Image Features
2.3.2 High Availability through Redundancy.
2.3.3 Fault-Tolerant Cluster Configurations
2.3.4 Checkpointing and Recovery Techniques
2.4 Cluster Job and Resource Management
2.4.1 Cluster Job Scheduling Methods
2.4.2 Cluster Job Management Systems.
2.4.3 Load Sharing Facility (LSF) for Cluster Computing
2.4.4 MOSIX: An OS for Linux Clusters and Clouds.
2.5 Case Studies of Top Supercomputer Systems.
2.5.1 Tianhe-1A: The World Fastest Supercomputer in 10
2.5.2 Cray XT5 Jaguar: The Top Supercomputer in 09
2.5.3 IBM Roadrunner: The Top Supercomputer in 08
2.6 Bibliographic Notes and Homework Problems
Acknowledgments. 1
References.
Homework Problems.
CHAPTER Virtual Machines and Virtualization of Clusters and Data
Centers.
Summary
3.1 Implementation Levels of Virtualization
3.1.1 Levels of Virtualization Implementation.
3.1.2 VMM Design Requirements and Providers.
3.1.3 Virtualization Support at the OS Level
3.1.4 Middleware Support for Virtualization
3.2 Virtualization Structures/Tools and Mechanisms.
3.2.1 Hypervisor and Xen Architecture.
3.2.2 Binary Translation with Full Virtualization.
3.2.3 Para-Virtualization with Compiler Support.
xii Contents
3.3 Virtualization of CPU, Memory, and I/O Devices.
3.3.1 Hardware Support for Virtualization
3.3.2 CPU Virtualization
3.3.3 Memory Virtualization.
3.3.4 I/O Virtualization150
3.3.5 Virtualization in Multi-Core Processors.
3.4 Virtual Clusters and Resource Management.
3.4.1 Physical versus Virtual Clusters
3.4.2 Live VM Migration Steps and Performance Effects.
3.4.3 Migration of Memory, Files, and Network Resources.
3.4.4 Dynamic Deployment of Virtual Clusters
3.5 Virtualization for Data-Center Automation
3.5.1 Server Consolidation in Data Centers
3.5.2 Virtual Storage Management. 1
3.5.3 Cloud OS for Virtualized Data Centers.
3.5.4 Trust Management in Virtualized Data Centers.
3.6 Bibliographic Notes and Homework Problems
Acknowledgments.
References.
Homework Problems.
PART COMPUTING CLOUDS, SERVICE-ORIENTED
ARCHITECTURE, AND PROGRAMMING
CHAPTER Cloud Platform Architecture over Virtualized Data
Centers
Summary
4.1 Cloud Computing and Service Models.
4.1.1 Public, Private, and Hybrid Clouds.
4.1.2 Cloud Ecosystem and Enabling Technologies.
4.1.3 Infrastructure-as-a-Service (IaaS)
4.1.4 Platform-as-a-Service (PaaS) and Software-as-a-Service
(SaaS).
4.2 Data-Center Design and Interconnection Networks206
4.2.1 Warehouse-Scale Data-Center Design206
4.2.2 Data-Center Interconnection Networks
4.2.3 Modular Data Center in Shipping Containers.
4.2.4 Interconnection of Modular Data Centers
4.2.5 Data-Center Management Issues
4.3 Architectural Design of Compute and Storage Clouds.
4.3.1 A Generic Cloud Architecture Design
4.3.2 Layered Cloud Architectural Development.
4.3.3 Virtualization Support and Disaster Recovery.
4.3.4 Architectural Design Challenges
Contents xiii
4.4 Public Cloud Platforms: GAE, AWS, and Azure
4.4.1 Public Clouds and Service Offerings.
4.4.2 Google App Engine (GAE)229
4.4.3 Amazon Web Services (AWS).
4.4.4 Microsoft Windows Azure.
4.5 Inter-cloud Resource Management
4.5.1 Extended Cloud Computing Services.
4.5.2 Resource Provisioning and Platform Deployment
4.5.3 Virtual Machine Creation and Management.
4.5.4 Global Exchange of Cloud Resources
4.6 Cloud Security and Trust Management.
4.6.1 Cloud Security Defense Strategies.
4.6.2 Distributed Intrusion/Anomaly Detection
4.6.3 Data and Software Protection Techniques
4.6.4 Reputation-Guided Protection of Data Centers
4.7 Bibliographic Notes and Homework Problems
Acknowledgements
References.
Homework Problems.
CHAPTER Service-Oriented Architectures for Distributed
Computing
Summary
5.1 Services and Service-Oriented Architecture
5.1.1 REST and Systems of Systems.
5.1.2 Services and Web Services.
5.1.3 Enterprise Multitier Architecture
5.1.4 Grid Services and OGSA.
5.1.5 Other Service-Oriented Architectures and Systems.
5.2 Message-Oriented Middleware
5.2.1 Enterprise Bus.
5.2.2 Publish-Subscribe Model and Notification
5.2.3 Queuing and Messaging Systems.
5.2.4 Cloud or Grid Middleware Applications.
5.3 Portals and Science Gateways
5.3.1 Science Gateway Exemplars
5.3.2 HUBzero Platform for Scientific Collaboration
5.3.3 Open Gateway Computing Environments (OGCE).
5.4 Discovery, Registries, Metadata, and Databases.
5.4.1 UDDI and Service Registries.
5.4.2 Databases and Publish-Subscribe
5.4.3 Metadata Catalogs308
5.4.4 Semantic Web and Grid
5.4.5 Job Execution Environments and Monitoring.
xiv Contents
5.5 Workflow in Service-Oriented Architectures.
5.5.1 Basic Workflow Concepts.315
5.5.2 Workflow Standards316
5.5.3 Workflow Architecture and Specification.
5.5.4 Workflow Execution Engine319
5.5.5 Scripting Workflow System Swift.
5.6 Bibliographic Notes and Homework Problems
Acknowledgements
References.
Homework Problems.
CHAPTER Cloud Programming and Software Environments.
Summary
6.1 Features of Cloud and Grid Platforms
6.1.1 Cloud Capabilities and Platform Features
6.1.2 Traditional Features Common to Grids and Clouds.
6.1.3 Data Features and Databases.
6.1.4 Programming and Runtime Support341
6.2 Parallel and Distributed Programming Paradigms
6.2.1 Parallel Computing and Programming Paradigms
6.2.2 MapReduce, Twister, and Iterative MapReduce.
6.2.3 Hadoop Library from Apache.355
6.2.4 Dryad and DryadLINQ from Microsoft.
6.2.5 Sawzall and Pig Latin High-Level Languages.
6.2.6 Mapping Applications to Parallel and Distributed
Systems
6.3 Programming Support of Google App Engine
6.3.1 Programming the Google App Engine
6.3.2 Google File System (GFS).
6.3.3 BigTable, Google’s NOSQL System
6.3.4 Chubby, Google’s Distributed Lock Service.
6.4 Programming on Amazon AWS and Microsoft Azure.
6.4.1 Programming on Amazon EC2.
6.4.2 Amazon Simple Storage Service (S3).
6.4.3 Amazon Elastic Block Store (EBS) and SimpleDB.
6.4.4 Microsoft Azure Programming Support.
6.5 Emerging Cloud Software Environments.
6.5.1 Open Source Eucalyptus and Nimbus.
6.5.2 OpenNebula, Sector/Sphere, and OpenStack.
6.5.3 Manjrasoft Aneka Cloud and Appliances.
6.6 Bibliographic Notes and Homework Problems399
Acknowledgement
References.
Homework Problems.
Contents xv
PART GRIDS, P2P, AND THE FUTURE INTERNET
CHAPTER Grid Computing Systems and Resource Management
Summary 16
7.1 Grid Architecture and Service Modeling.
7.1.1 Grid History and Service Families.
7.1.2 CPU Scavenging and Virtual Supercomputers419
7.1.3 Open Grid Services Architecture (OGSA)
7.1.4 Data-Intensive Grid Service Models425
7.2 Grid Projects and Grid Systems Built
7.2.1 National Grids and International Projects.
7.2.2 NSF TeraGrid in the United States.
7.2.3 DataGrid in the European Union
7.2.4 The ChinaGrid Design Experiences
7.3 Grid Resource Management and Brokering
7.3.1 Resource Management and Job Scheduling.
7.3.2 Grid Resource Monitoring with CGSP
7.3.3 Service Accounting and Economy Model
7.3.4 Resource Brokering with Gridbus.
7.4 Software and Middleware for Grid Computing
7.4.1 Open Source Grid Middleware Packages.
7.4.2 The Globus Toolkit Architecture (GT4).
7.4.3 Containers and Resources/Data Management.
7.4.4 The ChinaGrid Support Platform (CGSP)
7.5 Grid Application Trends and Security Measures
7.5.1 Grid Applications and Technology Fusion
7.5.2 Grid Workload and Performance Prediction.
7.5.3 Trust Models for Grid Security Enforcement
7.5.4 Authentication and Authorization Methods
7.5.5 Grid Security Infrastructure (GSI).
7.6 Bibliographic Notes and Homework Problems
Acknowledgments
References471
Homework Problems
CHAPTER Peer-to-Peer Computing and Overlay Networks
Summary
8.1 Peer-to-Peer Computing Systems.
8.1.1 Basic Concepts of P2P Computing Systems.
8.1.2 Fundamental Challenges in P2P Computing.
8.1.3 Taxonomy of P2P Network Systems.
8.2 P2P Overlay Networks and Properties
8.2.1 Unstructured P2P Overlay Networks
xvi Contents
8.2.2 Distributed Hash Tables (DHTs)
8.2.3 Structured P2P Overlay Networks.
8.2.4 Hierarchically Structured Overlay Networks
8.3 Routing, Proximity, and Fault Tolerance
8.3.1 Routing in P2P Overlay Networks.
8.3.2 Network Proximity in P2P Overlays
8.3.3 Fault Tolerance and Failure Recovery
8.3.4 Churn Resilience against Failures.
8.4 Trust, Reputation, and Security Management
8.4.1 Peer Trust and Reputation Systems
8.4.2 Trust Overlay and DHT Implementation
8.4.3 PowerTrust: A Scalable Reputation System.
8.4.4 Securing Overlays to Prevent DDoS Attacks.
8.5 P2P File Sharing and Copyright Protection
8.5.1 Fast Search, Replica, and Consistency
8.5.2 P2P Content Delivery Networks
8.5.3 Copyright Protection Issues and Solutions
8.5.4 Collusive Piracy Prevention in P2P Networks
8.6 Bibliographic Notes and Homework Problems
Acknowledgements
References
Homework Problems.
CHAPTER Ubiquitous Clouds and the Internet of Things
Summary
9.1 Cloud Trends in Supporting Ubiquitous Computing
9.1.1 Use of Clouds for HPC/HTC and Ubiquitous Computing
9.1.2 Large-Scale Private Clouds at NASA and CERN
9.1.3 Cloud Mashups for Agility and Scalability
9.1.4 Cloudlets for Mobile Cloud Computing
9.2 Performance of Distributed Systems and the Cloud
9.2.1 Review of Science and Research Clouds
9.2.2 Data-Intensive Scalable Computing (DISC)
9.2.3 Performance Metrics for HPC/HTC Systems
9.2.4 Quality of Service in Cloud Computing
9.2.5 Benchmarking MPI, Azure, EC2, MapReduce, and Hadoop
9.3 Enabling Technologies for the Internet of Things
9.3.1 The Internet of Things for Ubiquitous Computing
9.3.2 Radio-Frequency Identification (RFID)
9.3.3 Sensor Networks and ZigBee Technology
9.3.4 Global Positioning System (GPS)
9.4 Innovative Applications of the Internet of Things
9.4.1 Applications of the Internet of Things
Contents xvii
9.4.2 Retailing and Supply-Chain Management
9.4.3 Smart Power Grid and Smart Buildings
9.4.4 Cyber-Physical System (CPS)
9.5 Online Social and Professional Networking
9.5.1 Online Social Networking Characteristics
9.5.2 Graph-Theoretic Analysis of Social Networks
9.5.3 Communities and Applications of Social Networks
9.5.4 Facebook: The World’s Largest Social Network
9.5.5 Twitter for Microblogging, News, and Alert Services
9.6 Bibliographic Notes and Homework Problems
Acknowledgements
References.
Homework Problems
Index

章节摘录

版权页：   插图：   SUMMARY This chapter presents the evolutionary changes that have occurred in parallel,distributed,and cloudcomputing over the past 30 years,driven by applications with variable workloads and large datasets.We study both high-performance and high-throughput computing systems in parallel computersappearing as computer clusters,service-oriented architecture,computational grids,peer-to-peer networks,Internet clouds,and the Internet of Things.These systems are distinguished by their hardware architectures,OS platforms,processing algorithms,communication protocols,and servicemodels applied.We also introduce essential issues on the scalability,performance,availability,security,and energy efficiency in distributed systems. 1.1 SCALABLE COMPUTING OVER THE INTERNET Over the past 60 years,computing technology has undergone a series of platform and environmentchanges.In this section,we assess evolutionary changes in machine architecture,operating systemplatform,network connectivity,and application workload.Instead of using a centralized computerto solve computational problems,a parallel and distributed computing system uses multiplecomputers to solve large-scale problems over the Internet.Thus,distributed computing becomesdata-intensive and network-centric.This section identifies the applications of modern computersystems that practice parallel and distributed computing.These large-scale Internet applicationshave significantly enhanced the quality of life and information services in society today. 1.1.1 The Age of Internet Computing Billions of people use the Internet every day.As a result,supercomputer sites and large data centersmust provide high-performance computing services to huge numbers of Internet users concurrently.Because of this high demand,the Linpack Benchmark for high-performance computing(HPC)applications is no longer optimal for measuring system performance.The emergence of computingclouds instead demands high-throughput computing(HTC) systems built with parallel and distributed computing technologies [5,6,19,25].We have to upgrade data centers using fast servers,storagesystems,and high-bandwidth networks.The purpose is to advance network-based computing andweb services with the emerging new technologies. 1.1.1.1 The Platform Evolution Computer technology has gone through five generations of development,with each generation lastingfrom 10 to 20 years.Successive generations are overlapped in about 10 years.For instance,from1950 to 1970,a handful of mainframes,including the IBM 360 and CDC 6400,were built to satisfythe demands of large businesses and government organizations.From 1960 to 1980,lower-cost mini-computers such as the DEC PDP 11 and VAX Series became popular among small businesses and oncollege campuses.

媒体关注与评论

 “网格计算、对等计算、云计算这些新兴领域近几年日益受到学术界和工业界的关注。预计这些新技术将对商业、科学和工程及社会等众多方面产生巨大影响。本书的及时出版将会帮助读者了解分布式计算领域的最新技术。” —— Yi Pan, 佐治亚州立大学 “本书是一本全面而新颖的教材，内容覆盖高性能计算、分布式与云计算、虚拟化和网格计算。作者将应用与技术趋势相结合，揭示了计算的未来发展。无论是对在校学生还是经验丰富的实践者，本书都是一本优秀的读物。” ——Thomas J. Hacker, 普度大学

编辑推荐

《云计算与分布式系统:从并行处理到物联网(英文版)》编辑推荐：你是学习分布式系统或分布式计算课程的学生吗？如果是，那么《云计算与分布式系统:从并行处理到物联网(英文版)》是你的最佳选择。《云计算与分布式系统:从并行处理到物联网(英文版)》作者做了一项杰出的工作，《云计算与分布式系统:从并行处理到物联网(英文版)》中讲述了硬件和软件、系统体系结构、新的编程范式和生态系统方面的最新进展，既关注速度和性能优化，又考虑能源效率与节能。《云计算与分布式系统:从并行处理到物联网(英文版)》的目的是将传统的多处理器和多计算机集群转换成Web规模网格和云。也许更重要的是。《云计算与分布式系统:从并行处理到物联网(英文版)》关注未来互联网中泛在使用的对等网络，包括近年来快速发展的大型社会网络和物联网。

名人推荐

“网格计算、对等计算、云计算这些新兴领域近几年日益受到学术界和工业界的关注。预计这些新技术将对商业、科学和工程及社会等众多方面产生巨大影响。本书的及时出版将会帮助读者了解分布式计算领域的最新技术。” ——Yi Pan 佐治亚州立大学 “本书是一本全面而新颖的教材，内容覆盖高性能计算、分布式与云计算、虚拟化和网格计算。作者将应用与技术趋势相结合，揭示了计算的未来发展。无论是对在校学生还是经验丰富的实践者，本书都是一本优秀的读物。” ——Thomas J.Hacker 普度大学

用户评论 (总计38条)

•   原汁原味的原版书籍，内容对云计算和分布式系统进行了完整的介绍。书的质量不错，推荐。
•   系统阐述了云计算的起源及相关技术，尤其是云计算与分布式计算的关系。
•   云计算与分布式存储是现在的热门话题。
•   听别人说中文版的不是很好，就买了英文版的，顺便提升一些自己的英文阅读能力
•   非常经典的书，内容涵盖面很广泛，黄教授写的书很适合中国人阅读，全书英文都以断句为主，易读易懂。
•   虽然是英文，但是仔细看，讲述的还是很详细的
•   是本好书，黄楷博士的强烈推荐
•   感觉挺好 我看着应该会有点吃力，不过会提高英语水平的
•   挺厚的，全英文，考验英语水平啊！
•   很多概念，讲解浅显易懂。。。。
•   帮朋友买的 全英版本 据朋友反应 还不错
•   应该是本好书，d期待作者对这两个内容的描写
•   好书，质量不错，看了看内容也好，很详细
•   我觉得这本书对于想了解云计算、分布式系统相关知识的人，值得一读。
•   云计算现在应用已经比较广了，必须开始去了解了。
•   几年前看过黄凯的可扩展并行计算那本书，感觉可以！这本新作应该没有问题吧！
•   作为技术背景和知识的书，还是不错！比国内教授强多了哈！但实用性稍缺！
•   书刚刚拿到，学习中，感觉不错
•   书本很不错，印刷清晰，纸张也很厚，整体来说很满意～～～快递也很给力！！！
•   卖了以后没看下去……全英文，自己斟酌
•   结果点错了，就啃啃英文原著
•   书昨天刚到，所以对书的内容暂时不做评价。晚上翻了翻几下，看了几页，书就掉页了，估计是胶没粘好，而且封面被磕破了，这让我有一点伤心。
•   还行，应该还不错，主要是英文比较烂，读起来费点劲。内容比较全，涵盖方方面面，精简的描述。
•   不错，是正版 还比商场便宜好多
•   正如书名所指，内容涵盖了当今最热门的课题。虽然各章之间有逻辑关系，但可以只读所需要了解的那一部分。
•   质量不错，内容比较前沿。就是技术上介绍的比较少。
•   内容和纸张质量非常好，澄清了很多概念！
•   书的质量很好！快递速度也很快！内容还没用看！觉得蛮好的！老师推荐的教材！
•   书比想象的厚，比起原版便宜很多。
•   全部英文，英语不好的需要努力，书还是不错的，很实用
•   书本身纸质一般，平装书也就这样。事先填写的订单很明确的说发票要开“资料”，卖家还是开的“图书”。然后辩解说这是他们的规定。那你为什么不把规定写的清楚些？而是放在答读者问里，一个很难被发现的地方。既然不能按照我的需求开发票，你卖什么书？早说，我直接就换地方买了。
•   讲得太肤浅
•   英语版 经典
•   老外的书值得一看
•   挺好的书，讲的内容挺新的
•   帮朋友买的，应该是本好书
•   经典书籍，内容有点浅
•   科技前沿