Wiley Distributed Data Management For Grid Computing 2005 LinG OCR 7 0 2 6 LotB pdf (0471687197)

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Grid Computing is entering the IT mainstream driven by cost controls, business needs, and technology conditions. Developed by practitioners in the field, this book presents a balanced review of the field as well as an introduction to some of the more advanced concepts pivotal in real-world implementations. It also focuses on data management issues and techniques in Grid Computing. .

Table of Contents

Distributed Data Management for Grid Computing. .

Dedication. .

Acknowledgements. .

Preface. .

PART I. AN OVERVIEW OF GRID COMPUTING. .

Chapter 1. What is Grid Computing?

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Definition of Grid Computing. .

Leveling the Playing Field of Buzzword Mania. .

Paradigm Shift. .

Beyond Client/Server. .

New Topology. .

Chapter 2. Why Are Businesses Looking at Grid? .

History Repeats Itself. .

Early Needs. .

Artists and Engineers. .

The Whys and Wherefores of Grid. .

Financial Factors. .

Business Drivers. .

Technology& 8217;s Role. .

Chapter 3. Service-Oriented Architectures. .

What is Service-Oriented Architecture (SOA)? .

Driving Forces Behind SOA. .

Maturing Technology. .

Business. .

World Events. .

Enter Basic Supply and Demand Economics. .

Fundamental Shift in Computing. .

Chapter 4. Parallel Grid Planes. .

Using Art to Describe Life: Grid is the Borg. .

Grid Planes. .

Compute Grids. .

Data Grids. .

Compute and Data Grid - Parallel Planes. .

True Grid Must Include Data Management. .

Basic Data Management Requirements. .

Evolving the Data Grid. .

PART II. DATA MANAGEMENT IN GRID. .

Chapter 5. Scaling in the Grid Topology.

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Evolution in Data Management. .

Client/Server Evolution. .

Grid Evolution. .

Different Implementations of a Data Grid. .

Level Zero Data Grids. .

FTP in Grid. .

Distributed Filing Systems. .

Faster Servers. .

MetaData Hubs and Distributed Data Integration. .

Level 1 Data Grids. .

Foundations. .

Case Study: Integrasoft Grid Fabric (IGF). .

Application Characteristics for Grid. .

Chapter 6. Traditional Data Management.. .

Data Management. .

History. .

Features. .

Key for Usability. .

Chapter 7. Relational Data Management as a Baseline for Understanding Data Grid. .

Evolution of the Relational Model. .

Parallels to Data Management in Grid. .

Analysis of the Functional Tiers. .

Engines Determine the Type of Data Grid. .

Data Management Features. .

Chapter 8. Foundation of Comparing Data Grids. .

Core Engine Determines Performance and Flexibility. .

Replicated vs. Distributed. .

Centralized vs. Peer-to-Peer Synchronization. .

Access to the Data Grid. .

Support for Traditional Data Management Features. .

Support for Data Management Features Specific to Grid. .

Chapter 9. Data Regionalization. .

What are Data Regions? .

Data Regions in Traditional Terms. .

Data Management in a Data Grid. .

Data Distribution Policy. .

Data Distribution Policy Expression. .

Data Replication Policy. .

Data Replication Policy Expression. .

Synchronization Policy. .

Load and Store Policy. .

Data Load Policy Expression. .

Data Store Policy Expression. .

Event Notification Policy. .

Event Notification Policy Expression. .

Quality of Service (QoS) Levels. .

Chapter 10. Data Synchronization. .

Intra-Region Synchronization. .

Inter-Region Synchronization. .

Synchronization Architectures. .

Centralized Synchronization Manager. .

Peer-to-Peer Synchronization. .

Synchronization Patterns. .

Synchronization Granularity. .

Synchronization Policy Expression. .

Synchronization Pattern Simulations. .

Synchronization Policy as a Standard Interface. .

Chapter 11. Data Integration. .

Enterprise Application/Information Integration in Grid. .

STP, EAI, and EII. .

EII in Grid. .

Natural Separation of Process and Data. .

Data Load Policy. .

Data Store Policy. .

Load, Store, and Synchronization. .

Enterprise Data Grid Integration. .

Chapter 12. Data Affinity. .

A Measurable Quantity. .

What to Expect from Data Affinity. .

How to Achieve Data Affinity. .

Regionalization, Synchronization, Distribution and Data Affinity. .

Data Distribution is Key to Data Affinity. .

Data Affinity and Task Routing. .

Integration of Compute and Data Grids. .

Examples. .

PART III. PRACTICAL APPLICATIONS OF GRID. .

Chapter 13. What Applications are Good Candidates for the Grid.

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Grid Enabling Application Chrematistics. .

Grid& 8217;able Applications. .

Use Case Presentations. .

Chapter 14. Calculation Intensive Applications. .

Description. .

Use Cases. .

General Architecture. .

Data Grid Analysis. .

Chapter 15. Data Mining, Data Warehouses. .

Description. .

Use Cases. .

General Architecture. .

Data Grid Analysis. .

Benefits and Data Grid Specifics. .

Chapter 16. Geographic Boundary Problems. .

Description. .

Business Use Cases. .

General Architecture. .

Data Grid Analysis. .

Benefits and Data Grid Specifics. .

Chapter 17. Command and Control. .

Problem Description. .

Solution Architecture. .

Data Grid Analysis. .

Application Spin Offs. .

Chapter 18. Evolution to Web Services. .

Definition of Web Services. .

Description. .

Data Management: The Key Stone to Web Services. .

Web Services, Grid Infrastructures, and SONA. .

The Undiscovered Past. .

The SONA Model. .

Chapter 19. The Compute Utility. .

Overview. .

Architecture. .

PART IV. REFERENCE MATERIAL. .

Chapter 20. Language Interface.

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Programmatic. .

Query Based. .

XML Based. .

Chapter 21. Basic Programming Examples. .

Hello World Example. .

Coarse Granularity. .

Coarse Data Atom. .

Writer Program. .

Reader Program. .

Fine Granularity Example. .

Writer Program. .

Reader Program. .

Random Number Surface Example. .

Chapter 22. Additional Reading. .

Useful Information Sources. .

White Papers. .

Grid. .

GridFTP. .

Distributed File Systems. .

Standards Bodies. .

Globus - Data Grid. .

Global Grid Forum. .

W3C. .

Public and University Grid Efforts. .

Scientific Research Use of Grid. .

Web Services. .

Distributed Computing. .

Compute Utility. .

Service Oriented Architectures. .

Data Affinity. .

Chapter 23. White Paper. .

Natural Attraction Forces of Data Bodies Within a Data Grid To Describe Efficient Data Distribution Patterns. .

Introduction. .

Observation. .

Hypothesis. .

Laws of Attraction. .

How does this fit in with Data Distribution Patterns of Single Data Bodies within a Data Grid Fabric? .

Collision of Single Data Bodies. .

The Effects of the Data Grid on Single Data Body. .

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