Scope
1.1 Mashups and the Power of Web 2.0
The term mashup has its origins in the entertainment industry, where it describes the smart mixing of disparate musical tracks resulting in the creation of an altogether different musical product. The concept of a mashup in the digital age has evolved well beyond entertainment products and has taken on a much wider meaning. The term is now being applied to the dissolution of silos that had separated connectivity, data, applications, and decision-making and which results in completely new recipe for a service or application that is more attractive than the sum of its parts.
How will we define mashups in this study, and what makes them so attractive to carriers? To start with, mashups are all about devising working solutions from available means—with emphasis is on the means being already available. We define mashups as a smart combination of disparate, existing applications or services that come together on a network to yield a composite, coherent solution in an agile and economical way.
Thus mashups are not about genesis, but about synthesis. Given our definition, it should be readily apparent that mashups are inherently cost effective and time efficient. They may not be the most elegant solution for the requirement at hand, but certainly the quickest way to meet a market demand. The history of technology learning curves is testimony to the fact that elegance and efficiency will eventually seep into the DNA of new technology as the technology matures and best practices are identified, crystallized and updated. The optimism of the mashup stakeholder community about the future of this phenomena is therefore —in our opinion— justified; the skeptics notwithstanding.
There are no claims being made that we are aware of that would suggest that mashups are a panacea for all application design and development challenges. Clearly in business-critical applications, where the topmost priority of the application is…………………
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Market Segmentation
By geographical region
United States
Rest of North America
Europe, Middle East, Africa
Asia Pacific
Caribbean and Latin America
By access type
Wireless
Wireline
By revenue opportunity
Mashup data transfer revenue opportunity
Mashup access royalty revenue opportunity
Break down of mashup data transfer revenue opportunity by access type
(wireline versus wireless)
Geographical region break down mashup data transfer revenue opportunity
By application type:
Social Networking
LBS
Presence
VoIP
Messaging
SaaS
Conferencing
Streaming
Table of Contents
Table of Contents
Chapter I
EXECUTIVE SUMMARY
1.1 Mashups and the Power of Web 2.0
1.2 What We Found
1.3 What Role for Telcos in Mashups?
1.4 Mashup Market and Revenue Potential
Chapter II
INTRODUCTION TO MASHUPS
2.1 Definition and Classification of Mashups
2.2 Taxonomy of a Typical Mashup
2.3 Traction for Mashups
2.4 The Technology Underlying Mashups
2.4.1 Web 2.0
2.4.2 SOA
2.4.3 XML
2.4.4 Ajax
2.5 Reservations About Mashups
2.6 The Need for Standards
2.7 What Role for Telcos in Mashups?
Chapter III
TELCOS AND MASHUPS
3.1 What Mashups Mean for the Telcos
3.2 Why Mashups Now?
3.3 The Enabler is SIP
3.3.1 SIP’s Importance in Mashups
3.4 Social Networking
3.4.1 Social Networking Application Ecosystem
3.4.2 Mobile Social Networking
3.4.3 Social Networking and Mashups
3.4.4 Telco Perspective
3.5 Location Based Services
3.5.1 Mobile LBS
3.5.2 Map-Based LBS
3.5.3 LBS Mashups
3.6 VoIP
3.6.1 The VoIP Value Proposition
3.6.2 Decisive Traction for VoIP
3.6.3 VoIP and Mashups
3.6.4 The Telco Perspective
3.7 Presence
3.7.1 SIP and Presence
3.7.2 Mashups and Presence
3.7.3 The Telco Perspective
3.8 Messaging
3.8.1 SIP and Messaging
3.8.2 Mashups and Messaging
3.8.3 The Telco Perspective
3.9 Software as a Service
3.9.1 SaaS Implementation Methodology
3.9.2 SaaS and Mashups
3.9.3 The Telco Perspective
3.10 Conferencing
3.10.1 Metamorphosis
3.10.2 Conferencing and Mashups
3.10.3 The Telco Perspective
3.11 Streaming
3.11.1 SIP and Streaming
3.11.2 Streaming and Mashups
3.11.3 The Telco Perspective
3.12 Conclusion
Chapter IV
MASHUPS AND STAKEHOLDERS
4.1 Carrier Strategy Overview
4.1.1 BT
4.1.2 Vodafone
4.1.3 NTT Group
4.1.4 AT&T
4.1.5 SK Telecom
4.1.6 Telecom Italia
4.1.7 Rogers Communications
4.1.8 Sprint
4.2 Other Stakeholders
4.2.1 IBM
4.2.2 Microsoft
4.2.3 Serena Software
4.2.4 Nokia
4.2.5 eBay
4.2.6 Cisco Systems
4.2.7 Google
4.2.8 Yahoo! Inc.
4.2.9 BroadSoft
4.3 Conclusion
Chapter V
QUANTITATIVE ANALYSIS
5.1 The Telco Revenue Model
5.1.1 Data Transfer
5.1.2 Access Royalties
5.2 Research Methodology
5.2.1 What We Will Forecast
5.2.2 The Base Figures
5.2.3 Construction of the Market Model
5.3 Global Mashup Revenue Opportunity
5.4 Social Networking Revenue Opportunity
5.5 LBS Mashup Revenue Opportunity
5.6 Presence Mashup Revenue Opportunity
5.7 VoIP Mashup Revenue Opportunity
5.8 Messaging Mashup Revenue Opportunity
5.9 SaaS Mashup Revenue Opportunity
5.10 Conferencing Mashup Revenue Opportunity
5.11 Streaming Mashup Revenue Opportunity
5.12 Conclusion
List for Tables:
Table of Contents
Chapter I
EXECUTIVE SUMMARY
1.1 Mashups and the Power of Web 2.0
1.2 What We Found
1.3 What Role for Telcos in Mashups?
1.4 Mashup Market and Revenue Potential
Chapter II
INTRODUCTION TO MASHUPS
2.1 Definition and Classification of Mashups
2.2 Taxonomy of a Typical Mashup
2.3 Traction for Mashups
2.4 The Technology Underlying Mashups
2.4.1 Web 2.0
2.4.2 SOA
2.4.3 XML
2.4.4 Ajax
2.5 Reservations About Mashups
2.6 The Need for Standards
2.7 What Role for Telcos in Mashups?
Chapter III
TELCOS AND MASHUPS
3.1 What Mashups Mean for the Telcos
3.2 Why Mashups Now?
3.3 The Enabler is SIP
3.3.1 SIP’s Importance in Mashups
3.4 Social Networking
3.4.1 Social Networking Application Ecosystem
3.4.2 Mobile Social Networking
3.4.3 Social Networking and Mashups
3.4.4 Telco Perspective
3.5 Location Based Services
3.5.1 Mobile LBS
3.5.2 Map-Based LBS
3.5.3 LBS Mashups
3.6 VoIP
3.6.1 The VoIP Value Proposition
3.6.2 Decisive Traction for VoIP
3.6.3 VoIP and Mashups
3.6.4 The Telco Perspective
3.7 Presence
3.7.1 SIP and Presence
3.7.2 Mashups and Presence
3.7.3 The Telco Perspective
3.8 Messaging
3.8.1 SIP and Messaging
3.8.2 Mashups and Messaging
3.8.3 The Telco Perspective
3.9 Software as a Service
3.9.1 SaaS Implementation Methodology
3.9.2 SaaS and Mashups
3.9.3 The Telco Perspective
3.10 Conferencing
3.10.1 Metamorphosis
3.10.2 Conferencing and Mashups
3.10.3 The Telco Perspective
3.11 Streaming
3.11.1 SIP and Streaming
3.11.2 Streaming and Mashups
3.11.3 The Telco Perspective
3.12 Conclusion
Chapter IV
MASHUPS AND STAKEHOLDERS
4.1 Carrier Strategy Overview
4.1.1 BT
4.1.2 Vodafone
4.1.3 NTT Group
4.1.4 AT&T
4.1.5 SK Telecom
4.1.6 Telecom Italia
4.1.7 Rogers Communications
4.1.8 Sprint
4.2 Other Stakeholders
4.2.1 IBM
4.2.2 Microsoft
4.2.3 Serena Software
4.2.4 Nokia
4.2.5 eBay
4.2.6 Cisco Systems
4.2.7 Google
4.2.8 Yahoo! Inc.
4.2.9 BroadSoft
4.3 Conclusion
Chapter V
QUANTITATIVE ANALYSIS
5.1 The Telco Revenue Model
5.1.1 Data Transfer
5.1.2 Access Royalties
5.2 Research Methodology
5.2.1 What We Will Forecast
5.2.2 The Base Figures
5.2.3 Construction of the Market Model
5.3 Global Mashup Revenue Opportunity
5.4 Social Networking Revenue Opportunity
5.5 LBS Mashup Revenue Opportunity
5.6 Presence Mashup Revenue Opportunity
5.7 VoIP Mashup Revenue Opportunity
5.8 Messaging Mashup Revenue Opportunity
5.9 SaaS Mashup Revenue Opportunity
5.10 Conferencing Mashup Revenue Opportunity
5.11 Streaming Mashup Revenue Opportunity
5.12 Conclusion
Table of Tables
Chapter V
V-1 Global Mashup Revenue Opportunity for Telcos, 2010-2015
V-2 Dist. of Global Mashup Rev. Opp. for Telcos by Opp. Type, 2010-2015
V-3 Global Mashup Revenue Opportunity by Wireline vs. Wireless, 2010-2015
V-4 Regional Distribution of Global Mashup Revenue Opportunity, 2010-2015
V-5 Social Networking Mashup Revenue Opportunity, 2010-2015
V-6 Dist. of Social Networking Mashup Revenue Opp. by Type, 2010-2015
V-7 Social Networking Mashup Rev. Opp. by Wireline vs.Wireless, 2010-2015
V-8 Regional Dist. of Social Net. Mashup Rev. Opp. for Telcos, 2010-2015
V-9 LBS Mashup Revenue Opportunity, 2010-2015
V-10 Dist. of LBS Mashup Revenue Opportunity by Type, 2010-2015
V-11 Dist. of LBS Mashup Rev. Opp. by Wireline vs. Wireless, 2010-2015
V-12 Regional Distribution of LBS Mashup Revenue Opportunity, 2010-2015
V-13 Presence Mashup Revenue Opportunity, 2010-2015
V-14 Dist. of Presence Mashup Revenue Opp. by Type, 2010-2015
V-15 Dist. of Presence Mashup Rev. Opp. by Wireline vs. Wireless, 2010-2015
V-16 Regional Dist. of Presence Mashup Revenue Opportunity, 2010-2015
V-17 VoIP Mashup Revenue Opportunity, 2010-2015
V-18 Dist. of VoIP Mashup Revenue Opportunity by Type, 2010-2015
V-19 Dist. of VoIP Mashup Revenue Opp. by Wireline vs. Wireless, 2010-2015
V-20 Regional Dist. of VoIP Mashup Revenue Opp. for Telcos, 2010-2015
V-21 Messaging Mashup Revenue Opportunity for Telcos, 2010-2015
V-22 Distribution of Messaging Mashup Revenue Opp. by Type, 2010-2015
V-23 Distribution of Messaging Mashup Revenue Opp.by Wirelines vs. Wireless
V-24 Regional Dist. of Messaging Mashup Rev. Opp. for Telcos, 2010-2015
V-25 SaaS Mashup Revenue Opportunity for Telcos, 2010-2015
V-26 Distribution of SaaS Mashup Revenue Opportunity by Type, 2010-2015
V-27 Dist. of SaaS Mashup Rev. Opp. by Wireline vs. Wireless, 2010-2015
V-28 Regional Distribution of SaaS Mashup Rev. Opp. for Telcos, 2010-2015
V-29 Conferencing Mashup Revenue Opportunity, 2010-2015
V-30 Distribution of Conferencing Mashup Revenue Opp. by Type, 2010-2015
V-31 Dist. of Conf. Mashup Rev. Opp. by Wireline vs. Wireless, 2010-2015
V-32 Regional Distribution of Conferencing Mashup Revenue Opp., 2010-2015
V-33 Streaming Mashup Revenue Opp. for Telcos, 2010-2015
V-34 Dist. of Streaming Mashup Rev. Opportunity by Type, 2010-2015
V-35 Dist.of Streaming Mashup Rev. Opp.by Wireline vs. Wireless, 2010-2015
V-36 Regional Dist. of Streaming Mashup Revenue Op. for Telcos, 2010-2015
V-37 Mashup Revenue by Application Type Summary, 2010-2015
List for Figures:
Table of Figures
Chapter I
I-1 Logical Schematic of a Commercial Mashup
I-2 Global Mashup Revenue Opportunity for Telcos, 2010-2015
Chapter II
II-1 Logical Schematic of a Commercial Mashup
Chapter III
III-1 Seven Layers of OSI Model
III-2 Basic Components of a SIP Network
III-3 Example of a SIP Call Flow in Proxy Mode
III-4 Support for HTTP in SIP Setup
III-5 The Swimwire Mashup Homepage
III-6 The Twinkle Twitter Client for iPhone with the Near Me Tab Active
III-7 Schematic of the Ribbit SmartSwitch platform
III-8 Schematic of the BroadWorks Platform Offered by BroadSoft
III-9 OpSource On-Demand Platform
III-10 Schematic of the SaaS-enabled Mashup
Chapter IV
IV-1 Mashup Combining Twitter and Google Maps Conjured by Vodafone UK
IV-2 Schematic Representation of SAXAE Platform
IV-3 Speech Mashup Manager and Speech & Understanding Engine from AT&T Labs Research
IV-4 Customization of Mashups Facilitated by IBM Mashup Center
IV-5 Securing Information Assets as Facilitated by IBM Mashup Center
IV-6 Failed Initiative – Microsoft Popfly
IV-7 Schematic Representation of the Outlook Social Connector Function
IV-8 Business Mashups Product from Serena Software