Distributed Data Management in Grid Environments
暫譯: 網格環境中的分散式數據管理

Description:

Grid Computing is entering the IT mainstream driven by cost controls, business needs, and technology conditions. This book is developed by practitioners in the field and 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. It includes reasons why businesses are looking at Grid;data management in Grid; data regionalization, synchronization & integration, practical applications of Grid; and programming techniques & examples.

 

 

Table of Contents:

Foreword.

Preface.

Acknowledgements.

PART I: AN OVERVIEW OF GRID COMPUTING.

1. What is Grid Computing?

The Basics of Grid Computing.

Leveling the Playing Field of Buzzword Mania.

Paradigm Shift.

Beyond Client/Server.

New Topology.

2. Why Are Businesses Looking at Grid Computing?

History Repeats Itself.

Early Needs.

Artists and Engineers.

The Whys and Wherefores of Grid.

Financial Factors.

Business Drivers.

Technology's Role.

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.

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 COMPUTING.

5. Scaling in the Grid Topology.

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.

6. Traditional Data Management..

Data Management.

History.

Features.

Key for Usability.

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.

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.

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.

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.

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.

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 COMPUTING.

13. Which Applications are Good Candidates for the Grid.

Grid Enabling Application Chrematistics.

Grid'able Applications.

Use Case Presentations.

14. Calculation Intensive Applications.

Description.

Use Cases.

General Architecture.

Data Grid Analysis.

15. Data Mining, Data Warehouses.

Description.

Use Cases.

General Architecture.

Data Grid Analysis.

Benefits and Data Grid Specifics.

16. Geographic Boundary Problems.

Description.

Business Use Cases.

General Architecture.

Data Grid Analysis.

Benefits and Data Grid Specifics.

17. Command and Control.

Problem Description.

Solution Architecture.

Data Grid Analysis.

Application Spin Offs.

18. Web Services's Role in the SOA/SONA Evolution.

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.

19. The Compute Utility.

Overview.

Architecture.

PART IV: REFERENCE MATERIAL.

20. Language Interface.

Programmatic.

Query Based.

XML Based.

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.

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.

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.

Conclusions.

24. Glossary of Terms.

References.

Index.