Contents
Preface vii
About the Authors.
PART 1 SYSTEMS MODELING, CLUSTERING
AND VIRTUALIZATION 1
CHAPTER 1 Distributed System Models and Enabling Technologies3
Summary 4
1.1 Scalable Computing over the Internet 4
1.1.1 The Age of Internet Computing 4
1.1.2 Scalable Computing Trends and New Paradigms8
1.1.3 The Internet of Things and Cyber-Physical Systems 11
1.2 Technologies for Network-Based Systems.13
1.2.1 Multicore CPUs and Multithreading Technologies 14
1.2.2 GPU Computing to Exascale and Beyond. 17
1.2.3 Memory, Storage, and Wide-Area Networking. 20
1.2.4 Virtual Machines and Virtualization Middleware. 22
1.2.5 Data Center Virtualization for Cloud Computing. 25
1.3 System Models for Distributed and Cloud Computing.27
1.3.1 Clusters of Cooperative Computers.28
1.3.2 Grid Computing Infrastructures. 29
1.3.3 Peer-to-Peer Network Families32
1.3.4 Cloud Computing over the Internet.34
1.4 Software Environments for Distributed Systems and Clouds.36
1.4.1 Service-Oriented Architecture (SOA)37
1.4.2 Trends toward Distributed Operating Systems. 40
1.4.3 Parallel and Distributed Programming Models. 42
1.5 Performance, Security, and Energy Efficiency44
1.5.1 Performance Metrics and Scalability Analysis. 45
1.5.2 Fault Tolerance and System Availability.48
1.5.3 Network Threats and Data Integrity49
1.5.4 Energy Efficiency in Distributed Computing.51
1.6 Bibliographic Notes and Homework Problems. 55
Acknowledgments. 56
References 56
Homework Problems.58
Foreword. v
x
. .
CHAPTER 2 Computer Clusters for Scalable Parallel Computing65
Summary. 66
2.1 Clustering for Massive Parallelism 66
2.1.1 Cluster Development Trends66
2.1.2 Design Objectives of Computer Clusters.68
2.1.3 Fundamental Cluster Design Issues.69
2.1.4 Analysis of the Top 500 Supercomputers. 71
2.2 Computer Clusters and MPP Architectures75
2.2.1 Cluster Organization and Resource Sharing 76
2.2.2 Node Architectures and MPP Packaging.77
2.2.3 Cluster System Interconnects80
2.2.4 Hardware, Software, and Middleware Support. 83
2.2.5 GPU Clusters for Massive Parallelism83
2.3 Design Principles of Computer Clusters87
2.3.1 Single-System Image Features87
2.3.2 High Availability through Redundancy. 95
2.3.3 Fault-Tolerant Cluster Configurations99
2.3.4 Checkpointing and Recovery Techniques101
2.4 Cluster Job and Resource Management 104
2.4.1 Cluster Job Scheduling Methods 104
2.4.2 Cluster Job Management Systems.107
2.4.3 Load Sharing Facility (LSF) for Cluster Computing 109
2.4.4 MOSIX: An OS for Linux Clusters and Clouds. 110
2.5 Case Studies of Top Supercomputer Systems. 112
2.5.1 Tianhe-1A: The World Fastest Supercomputer in 2010. 112
2.5.2 Cray XT5 Jaguar: The Top Supercomputer in 2009 116
2.5.3 IBM Roadrunner: The Top Supercomputer in 2008. 119
2.6 Bibliographic Notes and Homework Problems120
Acknowledgments. 121
References.121
Homework Problems. 122
CHAPTER 3 Virtual Machines and Virtualization of Clusters and DataCenters. 129
Summary 130
3.1 Implementation Levels of Virtualization 130
3.1.1 Levels of Virtualization Implementation. 130
3.1.2 VMM Design Requirements and Providers.133
3.1.3 Virtualization Support at the OS Level 135
3.1.4 Middleware Support for Virtualization 138
3.2 Virtualization Structures/Tools and Mechanisms. 140
3.2.1 Hypervisor and Xen Architecture. 140
3.2.2 Binary Translation with Full Virtualization. 141
3.2.3 Para-Virtualization with Compiler Support.143
xii Contents
3.3 Virtualization of CPU, Memory, and I/O Devices.145
3.3.1 Hardware Support for Virtualization 145
3.3.2 CPU Virtualization 147
3.3.3 Memory Virtualization. 148
3.3.4 I/O Virtualization150
3.3.5 Virtualization in Multi-Core Processors. 153
3.4 Virtual Clusters and Resource Management.155
3.4.1 Physical versus Virtual Clusters156
3.4.2 Live VM Migration Steps and Performance Effects. 159
3.4.3 Migration of Memory, Files, and Network Resources.162
3.4.4 Dynamic Deployment of Virtual Clusters 165
3.5 Virtualization for Data-Center Automation 169
3.5.1 Server Consolidation in Data Centers169
3.5.2 Virtual Storage Management. 171
3.5.3 Cloud OS for Virtualized Data Centers. 172
3.5.4 Trust Management in Virtualized Data Centers. 176
3.6 Bibliographic Notes and Homework Problems179
Acknowledgments. 179
References. 180
Homework Problems. 183
PART 2 COMPUTING CLOUDS, SERVICE-ORIENTED
ARCHITECTURE, AND PROGRAMMING 189
CHAPTER 4 Cloud Platform Architecture over Virtualized Data Centers191
Summary 192
4.1 Cloud Computing and Service Models. 192
4.1.1 Public, Private, and Hybrid Clouds. 192
4.1.2 Cloud Ecosystem and Enabling Technologies. 196
4.1.3 Infrastructure-as-a-Service (IaaS) 200
4.1.4 Platform-as-a-Service (PaaS) and Software-as-a-Service(SaaS).203
4.2 Data-Center Design and Interconnection Networks206
4.2.1 Warehouse-Scale Data-Center Design206
4.2.2 Data-Center Interconnection Networks 208
4.2.3 Modular Data Center in Shipping Containers. 211
4.2.4 Interconnection of Modular Data Centers212
4.2.5 Data-Center Management Issues 213
4.3 Architectural Design of Compute and Storage Clouds. 215
4.3.1 A Generic Cloud Architecture Design 215
4.3.2 Layered Cloud Architectural Development.218
4.3.3 Virtualization Support and Disaster Recovery. 221
4.3.4 Architectural Design Challenges 225
Contents xiii
4.4 Public Cloud Platforms: GAE, AWS, and Azure 227
4.4.1 Public Clouds and Service Offerings. 227
4.4.2 Google App Engine (GAE)229
4.4.3 Amazon Web Services (AWS).231
4.4.4 Microsoft Windows Azure. 233
4.5 Inter-cloud Resource Management 234
4.5.1 Extended Cloud Computing Services. 235
4.5.2 Resource Provisioning and Platform Deployment 237
4.5.3 Virtual Machine Creation and Management. 243
4.5.4 Global Exchange of Cloud Resources246
4.6 Cloud Security and Trust Management. 249
4.6.1 Cloud Security Defense Strategies.249
4.6.2 Distributed Intrusion/Anomaly Detection253
4.6.3 Data and Software Protection Techniques 255
4.6.4 Reputation-Guided Protection of Data Centers257
4.7 Bibliographic Notes and Homework Problems261
Acknowledgements 261
References.261
Homework Problems. 265
CHAPTER 5 Service-Oriented Architectures for DistributedComputing271
Summary 272
5.1 Services and Service-Oriented Architecture 272
5.1.1 REST and Systems of Systems. 273
5.1.2 Services and Web Services. 277
5.1.3 Enterprise Multitier Architecture 282
5.1.4 Grid Services and OGSA.283
5.1.5 Other Service-Oriented Architectures and Systems.287
5.2 Message-Oriented Middleware289
5.2.1 Enterprise Bus. 289
5.2.2 Publish-Subscribe Model and Notification 291
5.2.3 Queuing and Messaging Systems.291
5.2.4 Cloud or Grid Middleware Applications. 291
5.3 Portals and Science Gateways294
5.3.1 Science Gateway Exemplars295
5.3.2 HUBzero Platform for Scientific Collaboration297
5.3.3 Open Gateway Computing Environments (OGCE). 301
5.4 Discovery, Registries, Metadata, and Databases. 304
5.4.1 UDDI and Service Registries. 304
5.4.2 Databases and Publish-Subscribe 307
5.4.3 Metadata Catalogs308
5.4.4 Semantic Web and Grid 309
5.4.5 Job Execution Environments and Monitoring. 312
xiv Contents
5.5 Workflow in Service-Oriented Architectures. 314
5.5.1 Basic Workflow Concepts.315
5.5.2 Workflow Standards316
5.5.3 Workflow Architecture and Specification. 317
5.5.4 Workflow Execution Engine319
5.5.5 Scripting Workflow System Swift. 321
5.6 Bibliographic Notes and Homework Problems322
Acknowledgements 324
References. 324
Homework Problems. 331
CHAPTER 6 Cloud Programming and Software Environments.335
Summary 336
6.1 Features of Cloud and Grid Platforms336
6.1.1 Cloud Capabilities and Platform Features 336
6.1.2 Traditional Features Common to Grids and Clouds. 336
6.1.3 Data Features and Databases. 340
6.1.4 Programming and Runtime Support341
6.2 Parallel and Distributed Programming Paradigms 343
6.2.1 Parallel Computing and Programming Paradigms 344
6.2.2 MapReduce, Twister, and Iterative MapReduce. 345
6.2.3 Hadoop Library from Apache.355
6.2.4 Dryad and DryadLINQ from Microsoft.359
6.2.5 Sawzall and Pig Latin High-Level Languages. 365
6.2.6 Mapping Applications to Parallel and Distributed Systems368
6.3 Programming Support of Google App Engine 370
6.3.1 Programming the Google App Engine 370
6.3.2 Google File System (GFS). 373
6.3.3 BigTable, Google’s NOSQL System376
6.3.4 Chubby, Google’s Distributed Lock Service. 379
6.4 Programming on Amazon AWS and Microsoft Azure. 379
6.4.1 Programming on Amazon EC2.380
6.4.2 Amazon Simple Storage Service (S3). 382
6.4.3 Amazon Elastic Block Store (EBS) and SimpleDB. 383
6.4.4 Microsoft Azure Programming Support.384
6.5 Emerging Cloud Software Environments. 387
6.5.1 Open Source Eucalyptus and Nimbus. 387
6.5.2 OpenNebula, Sector/Sphere, and OpenStack. 389
6.5.3 Manjrasoft Aneka Cloud and Appliances. 393
6.6 Bibliographic Notes and Homework Problems399
Acknowledgement 399
References. 399
Homework Problems. 405
Contents xv
PART 3 GRIDS, P2P, AND THE FUTURE INTERNET 413
CHAPTER 7 Grid Computing Systems and Resource Management 415
Summary 416
7.1 Grid Architecture and Service Modeling.416
7.1.1 Grid History and Service Families. 416
7.1.2 CPU Scavenging and Virtual Supercomputers419
7.1.3 Open Grid Services Architecture (OGSA) 422
7.1.4 Data-Intensive Grid Service Models425
7.2 Grid Projects and Grid Systems Built427
7.2.1 National Grids and International Projects. 428
7.2.2 NSF TeraGrid in the United States. 430
7.2.3 DataGrid in the European Union 431
7.2.4 The ChinaGrid Design Experiences434
7.3 Grid Resource Management and Brokering 435
7.3.1 Resource Management and Job Scheduling.435
7.3.2 Grid Resource Monitoring with CGSP 437
7.3.3 Service Accounting and Economy Model 439
7.3.4 Resource Brokering with Gridbus. 440
7.4 Software and Middleware for Grid Computing443
7.4.1 Open Source Grid Middleware Packages. 444
7.4.2 The Globus Toolkit Architecture (GT4).446
7.4.3 Containers and Resources/Data Management. 450
7.4.4 The ChinaGrid Support Platform (CGSP) 452
7.5 Grid Application Trends and Security Measures455
7.5.1 Grid Applications and Technology Fusion 456
7.5.2 Grid Workload and Performance Prediction. 457
7.5.3 Trust Models for Grid Security Enforcement 461
7.5.4 Authentication and Authorization Methods464
7.5.5 Grid Security Infrastructure (GSI).466
7.6 Bibliographic Notes and Homework Problems470
Acknowledgments 471
References471
Homework Problems 473
CHAPTER 8 Peer-to-Peer Computing and Overlay Networks 479
Summary 480
8.1 Peer-to-Peer Computing Systems. 480
8.1.1 Basic Concepts of P2P Computing Systems. 480
8.1.2 Fundamental Challenges in P2P Computing. 486
8.1.3 Taxonomy of P2P Network Systems. 490
8.2 P2P Overlay Networks and Properties492
8.2.1 Unstructured P2P Overlay Networks492
xvi Contents
8.2.2 Distributed Hash Tables (DHTs) 496
8.2.3 Structured P2P Overlay Networks.498
8.2.4 Hierarchically Structured Overlay Networks 501
8.3 Routing, Proximity, and Fault Tolerance505
8.3.1 Routing in P2P Overlay Networks. 505
8.3.2 Network Proximity in P2P Overlays507
8.3.3 Fault Tolerance and Failure Recovery 509
8.3.4 Churn Resilience against Failures.512
8.4 Trust, Reputation, and Security Management 514
8.4.1 Peer Trust and Reputation Systems 514
8.4.2 Trust Overlay and DHT Implementation517
8.4.3 PowerTrust: A Scalable Reputation System.520
8.4.4 Securing Overlays to Prevent DDoS Attacks. 522
8.5 P2P File Sharing and Copyright Protection 523
8.5.1 Fast Search, Replica, and Consistency 524
8.5.2 P2P Content Delivery Networks 529
8.5.3 Copyright Protection Issues and Solutions 533
8.5.4 Collusive Piracy Prevention in P2P Networks 535
8.6 Bibliographic Notes and Homework Problems538
Acknowledgements 538
References 539
Homework Problems. 541
CHAPTER 9 Ubiquitous Clouds and the Internet of Things 545
Summary 546
9.1 Cloud Trends in Supporting Ubiquitous Computing 546
9.1.1 Use of Clouds for HPC/HTC and Ubiquitous Computing 546
9.1.2 Large-Scale Private Clouds at NASA and CERN 552
9.1.3 Cloud Mashups for Agility and Scalability555
9.1.4 Cloudlets for Mobile Cloud Computing558
9.2 Performance of Distributed Systems and the Cloud 561
9.2.1 Review of Science and Research Clouds 562
9.2.2 Data-Intensive Scalable Computing (DISC)566
9.2.3 Performance Metrics for HPC/HTC Systems 568
9.2.4 Quality of Service in Cloud Computing 572
9.2.5 Benchmarking MPI, Azure, EC2, MapReduce, and Hadoop 574
9.3 Enabling Technologies for the Internet of Things 576
9.3.1 The Internet of Things for Ubiquitous Computing576
9.3.2 Radio-Frequency Identification (RFID)580
9.3.3 Sensor Networks and ZigBee Technology 582
9.3.4 Global Positioning System (GPS)587
9.4 Innovative Applications of the Internet of Things 590
9.4.1 Applications of the Internet of Things 591
Contents xvii
9.4.2 Retailing and Supply-Chain Management 591
9.4.3 Smart Power Grid and Smart Buildings 594
9.4.4 Cyber-Physical System (CPS)595
9.5 Online Social and Professional Networking597
9.5.1 Online Social Networking Characteristics 597
9.5.2 Graph-Theoretic Analysis of Social Networks 600
9.5.3 Communities and Applications of Social Networks 603
9.5.4 Facebook: The World’s Largest Social Network 608
9.5.5 Twitter for Microblogging, News, and Alert Services 611
9.6 Bibliographic Notes and Homework Problems 614
Acknowledgements 614
References.614
Homework Problems 618
Index 623
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