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More About This Title Distributed Data Management for Grid Computing
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With technology budgets under increasing scrutiny and system architecture becoming more and more complex, many organizations are rethinking how they manage and use technology. Keeping a strong business focus, this publication clearly demonstrates that the current ways of tying applications to dedicated hardware are no longer viable in today's competitive, bottom line-oriented environment. This evolution in distributed computing is leading a paradigm shift in leveraging widely distributed architectures to get the most processing power per IT dollar.
Presenting a solid foundation of data management issues and techniques, this practical book delves into grid architecture, services, practices, and much more, including:
* Why businesses should adopt grid computing
* How to master the fundamental concepts and programming techniques and apply them successfully to reach objectives
* How to maximize the value of existing IT investments
The author has tailored this publication for two distinct audiences. Business professionals will gain a better understanding of how grid computing improves productivity and performance, what impact it can have on their organization's bottom line, and the technical foundations necessary to discuss grid computing with their IT colleagues. Following the author's expert guidance and practical examples, IT professionals, architects, and developers will be equipped to initiate and carry out successful grid computing projects within their own organizations.
English
English
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.
