Librería Portfolio

Key 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


Description

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.

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