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Grid Computing: A Vertical Market Perspective 2005-2010
a market research report
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In Grid Computing: A Vertical Market Perspective 2005-2010, Insight Research explores the implications of grid computing on vertical markets and industries, with a special emphasis on the telecommunications industry. With its unique vantage point astride the telecom and IT industries, Insight analyzes both the risks and opportunities for service providers to implement grids for cost-cutting measures, and to capitalize on grids as revenue-generating sources.
Grid computing provides consistent, inexpensive access to computational resources (supercomputers, storage systems, data sources, instruments, and people) regardless of their physical location or access point. As such, The Grid provides a single, unified resource for solving large-scale compute and data intensive computing applications.
In Grid Computing: A Vertical Market Perspective, Insight examines grid technology, the players, and its industry-specific applications, offering segmented forecasts through 2010. In addition to an aggregated spending estimate for grid computing, this report forecasts spending in 14 vertical industries and four geographic regions. Revenue is also segmented by the sharing organization, and by the type of resource shared.
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Report Excerpt
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In the two years since INSIGHT’s last examination of the topic, grid computing has moved out of the laboratory and into mainstream commercial applications. No longer the exclusive tool of researchers seeking to harness enough compute power for massive computational challenges such as weather modeling or weapons test simulations, today grids are being deployed in more traditional commercial computing applications. For example, commercial computing stalwarts IBM, Intel, Hewlett-Packard (HP), and Sun recently announced they were forming the Globus Consortium to drive the technology into the mainstream for applications such as financial analysis, oil exploration, and pharmaceutical testing. And within the technical community, new standards being developed called the Web Services Resource Framework (WSRF) will foster convergence of the Web service and grid computing communities, which in the years ahead is likely to have a major impact on quality and diversity of Web services.
Grid computing is a form of distributed system wherein computing resources are shared across networks. Just as Web standards and technologies enabled universal, transparent access to documents, grid promises do so for computing resources. Grid enables the selection, aggregation, and sharing of information resources resident in multiple administrative domains and across geographic areas. These information resources are shared based upon their availability, capability, and cost, as well as the user’s quality of service (QoS) requirements. Grid computing is meant to:
· reduce total cost of ownership (TCO);
· aggregate and improve efficiency of computing, data, and storage resources; and
· enable the creation of virtual organizations for applications and data sharing.
IT analysts are calling grid computing one of the outstanding emerging technologies that will likely form the foundation of a fourth wave in IT. This nascent fourth stage of IT encompasses technologies and concepts such as grid computing, computing on demand, utility computing, organic information technology (IT), virtualization, adaptive computing, and Internet computing.
This new paradigm will enable heterogeneous computing resources of all kinds to be shared over networks and reallocated dynamically across applications, processes, and users to a greater degree than ever before possible. It will give office and even home machines the ability to reach into cyberspace, find resources wherever they may be, and assemble them on the fly into whatever applications are needed. In this respect, grid computing is a key foundational technology of this new paradigm.
Today there are nearly 100 substantial academic/research grids in development or production around the world, but the real action is in commercialization of grid technologies for the enterprise—and an area most pregnant with possibilities is the development of grid-enabled Web services.
In January 2004, a number of Web and grid computing specialists announced a set of draft specifications intended to quicken the pace of commercial Web services developments. The new WSRF is playing a role in converging the Web service and grid computing communities. To a certain extent, grids and Web services act alike: in both environments one system will make a request and another system will respond. Grids and Web services are different in respect to “state” memory. Web services are “stateless”—they have no memory of what a programmer has
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complete Executive Summary.
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Market Segmentation
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By Industry
Healthcare
Construction
Retail Trade
Wholesale Trade
Education/Social Services
Finance/Insurance/Real Estate
Professional Business Services
Hotel and Lodging
Transportation
Communications
Utilities
Entertainment and Media
Durable Manufacturing
Non-durable Manufacturing
By Region
North America
Europe/Middle East/Africa
Central America/Latin America
Asia/Pacific
By Ware
Hardware
Software
Professional Services
By Sharing Organization
Enterprise Grids
Partner Grids
Service Grids
By Resource Shared
Compute Grids
Data Grids
Instrumentation Grids
Application Grids
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Table of Contents
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GRID COMPUTING: A VERTICAL MARKET PERSPECTIVE 2005-2010
TABLE OF CONTENTS
Chapter I
EXECUTIVE SUMMARY
1.1 Grid Computing Background
1.2 Grid Computing Implications for Telecom
1.3 Grid Computing Market Analysis
Chapter II
OVERVIEW
2.1 Introduction to Grid Computing
2.1.1 Grid Computing Drivers
2.1.2 Grid Computing Inhibitors
2.1.3 Grid Computing Segmentation
2.2 Understanding Grids as a Tool for Resource Sharing
2.2.1 Compute Grids
2.2.2 Data Grids
2.2.3 Instrumentation Grids
2.2.4 Application Grids
2.3 Understanding Grids as Organizational Tools
2.3.1 Enterprise Grids
2.3.1.1 Cluster Grid
2.3.1.2 Campus Grid
2.3.1.3 Enterprise-wide Grid
2.3.2 Partner Grids
2.3.3 Service Grids
2.4 Related Computing Concepts
2.4.1 Supercomputers
2.4.2 Peer-to-Peer Computing
2.4.3 Service-Oriented Architectures
2.4.4 Utility Computing
2.4.5 Autonomic Computing
2.5 Grid Organizations and Standards
2.5.1 Global Grid Forum (GGF)
2.5.2 Open Grid Services Architecture (OGSA)
2.5.3 Web Services Resource Framework (WSRF)
2.5.4 The Globus Alliance
2.5.5 The Globus Toolkit
2.5.6 Enterprise Grid Alliance (EGA)
2.5.7 National Science Foundation (NSF) TeraGrid
Chapter III
APPLICATIONS
3.1 Introduction
3.2 Government and Academic Applications
3.2.1 Government-Sponsored Public Grid Efforts
3.2.1.1 North Carolina`s MCNC Start-Up Grid Program
3.2.1.2 West Virginia Global Grid Exchange
3.2.2 Physical Sciences Applications
3.2.2.1 Search for Extraterrestrial Intelligence (SETI)
3.2.2.2 Earthquake Engineering Simulation
3.2.2.3 High Energy Particle Physics and Earth Observation Applications
3.2.2.4 UK e-Science Program
3.2.3 Life Sciences Applications
3.2.3.1 Cancer Diagnosis and Screening
3.2.3.2 High Resolution Neurosciences Imaging
3.3 Commercial Applications
3.3.1 Pharmaceutical, Biomedical, and Biotechnological Applications
3.3.1.1 Pharmaceutical Research
3.3.1.2 Protein Analysis
3.3.2 Engineering and Design Automation Applications
3.3.2.1 Airplane Part Design
3.3.2.2 Computer Chip Design
3.3.2.3 Computer Animation and Video Postproduction
3.3.2.4 Aerial and Satellite Image Distribution
3.3.3 Financial Services Applications
3.3.6.1 Investment Banking Applications
3.3.6.2 Life Insurance Financial Modeling Application
3.3.6.3 Risk Management Applications
3.3.6.4 Wachovia Bank
3.3.4 Human Resources Application
3.3.5 Enterprise Data Center Back-up Solution
3.3.6 Information Services Application
3.4 Consumer Applications
Chapter IV
IMPLICATIONS FOR TELECOM
4.1 Grid Computing Implications for Telecom
4.1.1 IT Operations
4.1.2 Bandwidth and Traffic Patterns
4.1.3 Excess Capacity
4.1.4 Next-Generation Telco Services
4.1.5 Adoption Phases
4.1.6 Potential Roles for Telcos
4.2 Applications Best Suited for Grid Computing
4.2.1 TeraGrid Case Study
4.2.2 Level 3 Case Study
4.2.3 British Telecommunications (BT) Case Study
4.2.4 OptIPuter Project
4.3 Global Adoption of Grid Technologies
Chapter V
VENDORS
5.1 Introduction
5.2 Major IT Platform Providers
5.2.1 International Business Machines (IBM)
5.2.1.1 Background
5.2.1.2 e-Business On Demand
5.2.1.3 IBM and Grid Computing
5.2.2 Hewlett-Packard (HP)
5.2.2.1 Background
5.2.2.2 Grid Solution Stack
5.2.2.3 HP`s Next Phase Of Utility Computing
5.2.3 Sun Microsystems
5.2.3.1 Background
5.2.3.2 Sun N1
5.2.3.3 Open Net Environment (ONE) Grid Engine
5.2.3.4 Utility Computing Services
5.2.5 Gateway
5.2.6 Dell
5.2.7 Apple Computer
5.3 Grid Independent Software Companies
5.3.1 Avaki
5.3.1.1 Background
5.3.1.2 Target Markets
5.3.1.3 Technology and Products
5.3.2 DataSynapse, Inc.
5.3.2.1 Background
5.3.2.2 Target Markets
5.3.2.3 Technology and Products
5.3.3 Platform Computing, Inc.
5.3.3.1 Background
5.3.3.2 Target Markets
5.3.3.3 Technology and Products
5.3.3.4 Services
5.3.3.5 Partnerships
5.3.4 United Devices
5.3.4.1 Background
5.3.4.2 Target Markets
5.3.4.3 Technology and Products
5.3.4.4 Business Model and Partnerships
5.3.5 Entropia, Inc.
5.3.5.1 Background
5.3.5.2 Target Markets
5.3.5.3 Technology and Products
5.3.5.4 Business Model
5.3.6 GridSystems
5.3.6.1 Background
5.3.6.2 Target Markets
5.3.6.3 Technology and Products
5.3.7 Univa
5.3.8 Base One International
5.3.9 Tsunami Research
Chapter VI
MARKET FORECAST
6.1 Overview
6.1.1 Methodology
6.1.2 Market Segmentation
6.2 Market Model Assumptions
6.2.1 Aggregated IT and Grid Spending
6.2.2 IT and Grid Spending by Vertical Markets
6.2.3 IT and Grid Spending by Region
6.2.4 IT and Grid Spending by Component
6.2.5 Grid Spending by Organization
6.2.6 Grid Spending by Resource
6.3 Forecasts Summary
Appendix
GLOSSARY
Table of Figures
Chapter I
I-1 Grid Computing as Part of the IT Evolution
I-2 Worldwide Grid Spending by Type of Organization, 2005-2010 ($Billions)
Chapter II
II-1 Grid Computing as Part of the IT Evolution
II-2 Grand Synthesis
II-3 Compute Grid Operation
II-4 Evolution of Grids
II-5 Service Oriented Architecture
II-6 Web Services as an SOA
II-7 Grid Architecture
Chapter III
III-1 Biotech and Pharmaceutical Companies` Data Management Challenges
III-2 Ad Hoc Solutions Used to Address Data Management Problems
Chapter IV
IV-1 TeraGrid Backplane Architecture
IV-2 TeraGrid National Architecture
IV-3 TeraGrid Site Architecture
Chapter V
V-1 IBM Schematic for On-demand Business
V-2 HP`s Grid Solution Stack Diagram
TABLE OF TABLES
Chapter I
I-1 Grid Market Segmentation by Resource
I-2 Grid Market Segmentation by Organization
Chapter II
II-1 Server and Storage Resource Utilization
II-2 Grid Market Segmentation by Type of Resource
II-3 Grid Market Segmentation by Type of Organization
II-4 Supercomputer Distinctions
II-5 Utility Pricing Plans
II-6 Autonomic Computing Attributes
II-7 Web Services Resource Framework Specifications
Chapter III
III-1 Commercial Applications of Grid Computing
III-2 Phased Introduction of Grid Applications
Chapter V
V-1 Grid Vendor Landscape
Chapter VI
VI-1 Grid Market Segmentation by Geography
VI-2 Grid Market Segmentation by Component
VI-3 Grid Market Segmentation by Type of Resource
VI-4 Grid Market Segmentation by Type of Organization
VI-5 Worldwide IT Spending, 2005-2010 ($Billions)
VI-6 Worldwide Grid Spending, 2005-2010 ($Millions)
VI-7 Worldwide IT Spending by Vertical, 2005-2010 ($Billions)
VI-8 Worldwide Grid Computing by Vertical Market, 2005-20010 ($Billions)
VI-9 Worldwide IT Spending by Region, 2005-2010 ($Billions)
VI-10 Worldwide Grid Spending by Region, 2005-2010 ($Billions)
VI-11 Worldwide IT Spending by Component, 2005-2010 ($Billions)
VI-12 Worldwide Grid Spending by Component, 2005-2010 ($Billions)
VI-13 Worldwide Grid Spending by Type of Organization, 2005-2010 ($Billions)
VI-14 Worldwide Grid Spending by Type of Resource, 2005-2010 ($Billions)
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Pricing Information
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Hard Copy
Price
$ 1998
Electronic Copy Price
(PDF License Descriptions)
$ 2348 Single-User Printable PDF
$ 3498 6-Seat Printable PDF
$ 5000 Unlimited Corporate-Wide Distribution
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