Distributed Data Management in Grid Environments

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.

描述：
網格計算正進入IT主流，受到成本控制、業務需求和技術條件的推動。本書由該領域的從業人員開發，提供了對該領域的平衡評論，以及一些在實際應用中至關重要的高級概念的介紹。它還關注網格計算中的數據管理問題和技術。它包括企業看重網格的原因；網格中的數據管理；數據區域化、同步和集成；網格的實際應用；以及編程技術和示例。

目錄：
前言。
前言。
致謝。
第一部分：網格計算概述。
1. 什麼是網格計算？
網格計算的基礎知識。
平衡流行詞的競爭優勢。
範式轉變。
超越客戶/服務器。
新的拓撲結構。
2. 為什麼企業看重網格計算？
歷史重演。
早期需求。
藝術家和工程師。
網格的原因和目的。
財務因素。
業務驅動因素。
技術的角色。
3. 面向服務的架構。
什麼是面向服務的架構（SOA）？
推動SOA的力量。
成熟的技術。
商業。
世界事件。
基本供需經濟學。
計算的基本轉變。
4. 平行網格平面。
用藝術來描述生活：網格就是博格。
網格平面。
計算網格。
數據網格。
計算和數據網格-平行平面。
真正的網格必須包括數據管理。
基本數據管理要求。
發展數據網格。
第二部分：網格計算中的數據管理。
5. 網格拓撲中的擴展。
數據管理的演進。
客戶/服務器演進。
網格演進。
數據網格的不同實現。
零級數據網格。