July 23, 2012
??[MK] Todd
New! Instructors? resources now available
Visit our textbook resource site to obtain materials designed to facilitate the classroom experience, including:
- PowerPoint slides to enhance lectures
- Solutions for selected exercises in the book
- All figure files for instructors to incorporate in their own presentations
About the Book:
From the leading minds in the field, Distributed and Cloud Computing is the first modern, up-to-date distributed systems textbook. Starting with an overview of modern distributed models, the book exposes the design principles, systems architecture, and innovative applications of parallel, distributed, and cloud computing systems. It will teach you how to create high-performance, scalable, reliable systems, providing comprehensive coverage of distributed and cloud computing, including:
- Facilitating management, debugging, migration, and disaster recovery through virtualization
- Clustered systems for research or ecommerce applications
- Designing systems as web services
- Social networking systems using peer-to-peer computing
- Principles of cloud computing using examples from open-source and commercial applications
Using examples from open-source and commercial vendors, the text describes cloud-based systems for research, e-commerce, social networking and more.
Features:
- Complete coverage of modern distributed computing technology including clusters, the grid, service-oriented architecture, massively parallel processors, peer-to-peer networking, and cloud computing
- Includes case studies from the leading distributed computing vendors: Amazon, Microsoft, Google, and more
- Designed to meet the needs of students taking a distributed systems course, each chapter includes exercises and further reading, with lecture slides and solutions available online
Table of Contents
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 The Age of Internet Computing
1.1.2 Computing Trends and New Paradigms
1.1.3 Internet of Things and Cyber-Physical Systems
1.2 Technologies for Network-based Computing
1.2.1 Multicore, Many-Core and Multithreading Technologies
1.2.2 GPU Computing To Exascale and Beyond
1.2.3 Memory, Storage and System-Area Networking
1.2.4 Virtual Machines and Virtualization Middleware
1.2.5 Datacenter 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 Distributed Operating Systems and Software Tools
1.4.3 Parallel/Distributed Programming Models
1.5 Performance, Security, and Energy-Efficiency
1.5.1 Performance Metrics and System Scalability
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
Chapter 2: Computer Clusters for Scalable Computing
2.1 Clustering for Massive Parallelism
2.1.1 Historical Cluster Development Trends
2.1.2 Design Objectives of Computer Clusters
2.1.3 Fundamental Cluster Design Issues
2.1.4 Analysis of Top-500 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 Images 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 Supercomputyers and MPP Systems
2.5.1 Tianhe-1A: The World Fastest Supercomputer in 2010
2.5.2 Cray XT-5 Jaguar : The Top Supercomputer in 2009
2.5.3 IBM RoadRunner: The Top Supercomputer in 2008
2.5.4 Nebulae: China?s First Petascale Supercomputer
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 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 or Library Support for Virtualization
3.2 Virtualization Structures/Tools and Mechanisms
3.2.1 Hypervisor and XEN Architectures
3.2.2 Binary Translation with Full Virtualization
3.2.3 Para Virtualization with Compiler Support
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 Virtualization
3.3.5 Multi-core Virtualization
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, File and Network Resources
3.4.4 Dynamic Deployment of Virtual Clusters
3.5 Virtualization for Datacenter Automation
3.5.1 Server Consolidation in Datacenters
3.5.2 Virtual Storage Management
3.5.3 Cloud OS for Virtualizing Datacenters
3.5.4 Trust Management in Datacenter Design
3.6 Bibliographic Notes and Homework Problems
Part 2: Computing Clouds and Service-Oriented Architecture
Chapter 4: Design of Cloud Computing Platforms
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) Model
4.1.4 Platform- and Software-as-a-Service (Paas, SaaS)
4.2 Datacenter Design and Interconnection Networks
4.2.1 Warehouse-Scale Datacenter Design
4.2.2 Datacenter Interconnections Networks
4.2.3 Modular Datacenter in Truck Container
4.2.4 Interconnection of Modular datacenters
4.2.5 Datacenter Management Issues
4.3 Architecture 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
4.4 Public Cloud Platforms: GAE, AWS and Windows Azure
4.4.1 Public Clouds and Service Offerings
4.4.2 Google Application Engine (GAE)
4.4.3 Amazon Web Service (AWS)
4.4.4 Microsoft Windows Azure
4.5 Cloud Resource Management and Exchanges
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 Datacenters
4.7 References and Homework Problems
Chapter 5: Service Oriented Architectures
5.1 Services and Service Oriented Architectures
5.1.1 REST and Systems of Systems
5.1.2 Services and Web Services
5.1.3 Enterprise Multi-tier 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 Illustrative Examples of Middleware
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
5.3.4 Summary and Future Developments
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 catalogues
5.4.4 Semantic Web and Grid
5.4.5 Job Execution Environments and Monitoring
5.5 Workflow in Service-Oriented Architectures
5.5.1 Basic Concepts of Workflow
5.5.2 Workflow Standards
5.5.3 Workflow Architecture and Specification
5.5.4 Workflow Execution Engine
5.5.5 Example of a Scripting Workflow System
5.6 Bibliographic Notes and Homework Problems
Chapter 6: Cloud Programming and Software Environments
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 Features
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
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 Amazon Web Services (AWS) Programming
6.4.1 AWS Platform and Service Offerings
6.4.2 Amazon Elastic Compute Cloud EC2
6.4.3 Amazon Simple Storage Service S3
6.4.4 Amazon Elastic Block Store EBS and SimpleDB
6.5 Microsoft Azure Programming Support
6.5.1 Azure Cloud Platform
6.5.2 Programming Azure
6.6 Emerging Cloud Software Environments
6.6.1 Open Source Eucalyptus and Nimbus
6.6.2 OpenNebula, Sector/Sphere, and OpenStack
6.6.3 Manjrasoft Aneka Cloud and Appliances
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
7.1.1 Grid Categories and Service Protocols
7.1.2 Resource Aggregation and Virtual Organizations
7.1.3 Open Grid Services Architecture (OGSA)
7.1.4 Data-Intensive Grid Service Models
7.2 Case Studies of Grid Computing Systems
7.2.1 National Grid Development Projects
7.2.2 The NSF TeraGrid in The USA
7.2.3 The DataGrid built by 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 ? The CGSV Experiences
7.3.3 Service Accounting and Economy Model
7.3.4 Grid Resource Brokering -The Gridbus Experiences
7.4 Middleware Support for Grid Resource Management
7.4.1 Open-Source Grid Middleware Packages
7.4.2 The Globus Toolkit Architecture (GT4)
7.4.3 Globus Containers and Resource/Data Management
7.4.4 The ChinaGrid Support Platform (CGSP)
7.5 Grid Security Infrastructure in GT4
7.5.1 Grid security Trust Models
7.5.2 Authentication and Authorization
7.5.3 Globus Security Infrastructure (GSI)
7.6 Bibliographic Notes and Homework Problems
Chapter 8: P2P Computing with Overlay Networks
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
8.2.2 Distributed Hash Tables (DHT)
8.2.3 Structured P2P Overlay Networks
8.2.4 Hybrid P2P 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 and Reputation 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
8.5 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
Chapter 9: Ubiquitous Computing with Clouds and The Internet of Things
9.1 Cloud Trend To Support Ubiquitous Computing
9.1.1 Use of Clouds for HPC and Ubiquitous Computing
9.1.2 Large-Scale Private Clouds (NASA, CERN, etc.)
9.1.3 Cloud Mashup for Agility and Scalability
9.1.4 Cloudlets for Mobile Cloud Computing
9.1.5 Review of Science and Research Clouds
9.2 Performance Metrics for HPC and HTC Systems
9.2.1 Data-Intensive Scalable Computing (DISC)
9.2.2 Performance Metrics for HPC Systems
9.2.3 Quality of Service of HTC Systems
9.2.4 Workload Characterization for Performance Prediction
9.2.5 Benchmarking MPI, Azure, EC2, MapReduce, Hadoop
9.3 Enabling Technologies for The Internet of Things
9.3.1 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 Systems (GPS)
9.4 Innovative Applications of The Internet of Things
9.4.1 Applications of The Internet of Things
9.4.2 Retailing and Supply-Chain Management
9.4.3 Smart Power Grid and Smart Buildings
9.4.4 Cyber-Physical Systems (CPS)
9.5 On-Line Social and Professional Networking
9.5.1 Online Social Network 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 Content-Sharing Network
9.5.5 Twitter for Microblogging, News and Alert Services
9.6 Bibliographic Notes and Homework Problems
ISBN: 9780123858801 | View in bookstore
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