多媒體行動內容發布

The migration and distribution of multimedia web content to mobile devices has only just scratched the surface. There is expected to be an explosive growth in mobile content in the next 5 to 10 years. Revolutionary audio and video rich mobile devices capable of accessing multiple mobile and wireless networks concurrently will shape the future of mobile content distribution technologies. Combining this with people' s willingness to communicate anytime, anywhere will redefine key assumptions that govern the delivery of content into the mobile world.

Traditionally mobile content has always been fed from the content distributor or publisher to the end-user. However, the rising popularity of user-generated content, which in turn is being driven by trends like mobile social networking, citizen journalism and the ubiquitous presence of camera phones, is leading to mobile content being shared between end-users. Currently the sharing of mobile content is done using a client-server based architecture, which is not the most efficient way of sharing content.

The key value addition that will enable effective and efficient mobile content distribution will stem from the re-engineering of the mobile content network architecture itself. This refers to the emergence of distributed peer to peer architectures replacing the current client server based architectures.

This report highlights opportunities within the mobile content distribution market, as well as emerging threats and concerns of how new technologies might impact the current content delivery model.

• Evolutionary sketch of the content distribution paradigm of the web
• Emerging trends that help shape the future of mobile content distribution
• Mobile content distribution value chain analysis
• Exploring strategies for content value chain players
• Market forecasts of the mobile content distribution market

Overall, the report aims to provide mobile network operators, content distribution network operators, content publishers, web advertisers and content owners a fresh perspective and a strategic rethink of the mobile content distribution market and the opportunities within it. It also explores the key question whether the peer-to-peer collaborative paradigm is likely to have a disruptive

Table of Contents

• 1.1 Overview
• 1.2 Forecast
• 1.3 Major Conclusions

• Exhibit 1.1: Multi-modality, Session Management and Peer to Peer Augmented Techniques in a Mobile Content Distribution Network
• Exhibit 1.2: Disruption in Mobile Content Value Chain
• Exhibit 1.3: Fisher-Pry Model
• Exhibit 1.4: Gompertz Curve
• Exhibit 1.5: Exhibit 1.5: Revenue Opportunity at Risk as a % of Total Multimedia Mobile Content Revenue Opportunity - Chart

• 2.1 Emergence of Mobile Content Distribution Network
• 2.2 Mobile Content Classification
  • 2.2.1 Packetized Data
  • 2.2.2 Packetized Stream
  • 2.2.3 Broadcast
• 2.3 Multimedia Mobile Content Distribution Market

• Exhibit 2.1: Mobile Oriented Content Classification
• Exhibit 2.3: Global Multimedia Mobile Content Distribution Revenues (in US$ millions)
• Exhibit 2.2: Global Multimedia Mobile Content Distribution Traffic

• 3.1 Content Distribution Architectures in Internet
  • 3.1.1 Forward and Reverse Proxies
  • 3.1.2 Content Distribution Network
  • 3.1.3 Peer-to-Peer Network
  • 3.1.4 Competitive Landscape
• 3.2 Content Distribution in Mobile Internet
  • 3.2.1 Station-Mobile Architecture and Applications
  • 3.2.2 Proxy-based Architectural Augmentation and Applications
  • 3.2.3 A Case Study: Zannel

• Exhibit 3.1: Client Server Architectures
• Exhibit 3.2: Content Delivery Example (without Content Distribution Network)
• Exhibit 3.3: Forward Proxy Architecture
• Exhibit 3.4: Reverse Proxy Architecture
• Exhibit 3.5: Content Distribution Architecture
• Exhibit 3.6: Content Delivery Example (with CDN)
• Exhibit 3.7: Comparison of Akamai vs. Limelight
• Exhibit 3.8: Peer-to-Peer Network
• Exhibit 3.9: Classification of Peer-to-Peer Networks
• Exhibit 3.10: Content Distribution Competitive Landscape
• Exhibit 3.11: Basic Wireless Communication Architecture
• Exhibit 3.12: Station-Mobile Distribution Architecture
• Exhibit 3.13: Proxy augmented Mobile oriented Distribution Architecture
• Exhibit 3.14: Zannel Proxying Architecture

• 4.1 Mobile Content Distribution Network
  • 4.1.1 Multi-modality
  • 4.1.2 Session Management
• 4.2 Peer-to-Peer and Mobile Content Distribution Network
  • 4.2.1 Peer-to-Peer assisted Mobile Content Distribution Network
  • 4.2.2 Peer-to-Peer Augmented Mobile Content Distribution Network

• Exhibit 4.1: Multi-modality - Separating Control from Data
• Exhibit 4.2: Session Management - Mobile Forward and Mobile Reverse Proxies
• Exhibit 4.3: Session Management - Always Best Connected
• Exhibit 4.4: Session Management - Spliced Content Delivery
• Exhibit 4.5: Peer-to-Peer assisted Mobile Content Distribution
• Exhibit 4.6: Peer-to-Peer augmented Mobile Content Distribution
• Exhibit 4.7: P2P Assisted Distribution vs. P2P Augmented Distribution

• 5.1 Content Distribution Value Chain Analysis
  • 5.1.1 Key Players
  • 5.1.2 Cost Model
  • 5.1.3 Multimedia Mobile Content Distribution Value Chain
• 5.2 Market Forecast Methodology
  • 5.2.1 Fisher-Pry Model
  • 5.2.2 Gompertz Curve
  • 5.2.3 Methodology Flowchart
• 5.3 Market Forecasts
  • 5.3.1 Multimedia Mobile Content Distribution Revenues
  • 5.3.2 Multimedia Mobile Content Distribution Traffic
  • 5.3.3 Multimedia Mobile Content Distribution Traffic using Alternative Routing Techniques
  • 5.3.4 Multimedia Mobile Content Distribution Revenues Affected by Alternate Route

• Exhibit 5.1: Content Distribution Value Chain
• Exhibit 5.2: Cost Model
• Exhibit 5.3: Disruption in Mobile Content Value Chain
• Exhibit 5.4: Fisher-Pry Model
• Exhibit 5.5: Gompertz Curve
• Exhibit 5.6: Basic Methodology for Forecasts
• Exhibit 5.7: Multimedia Mobile Content Distribution Revenues (in US$ millions) - By Geography (Chart)
• Exhibit 5.8: Multimedia Mobile Content Distribution Revenues (in US$ millions) - By Geography (Table)
• Exhibit 5.9: Multimedia Mobile Content Distribution Revenues (in US$ millions) - By Traffic Type (Chart)
• Exhibit 5.10: Multimedia Mobile Content Distribution Revenues (in US$ millions) - By Traffic Type (Table)
• Exhibit 5.11: Multimedia Mobile Content Distribution Revenues (in US$ millions) - By Traffic and Geography 2007 (Chart)
• Exhibit 5.12: Multimedia Mobile Content Distribution Revenues (in US$ millions) - By Traffic and Geography 2007 (Table)
• Exhibit 5.13: Multimedia Mobile Content Distribution Revenues (in US$ millions) - By Traffic and Geography 2012 (Chart)
• Exhibit 5.14: Multimedia Mobile Content Distribution Revenues (in US$ millions) - By Traffic and Geography 2012 (Table)
• Exhibit 5.15: Multimedia Mobile Content Distribution Traffic (Units/Subs in millions) - (Table)
• Exhibit 5.16: Global Estimated MMCD Traffic Using Alternative Distribution Mechanisms (%) - Chart
• Exhibit 5.17: Global Estimated MMCD Traffic Using Alternative Distribution Mechanisms (%) - Table
• Exhibit 5.18: Traffic Breakup of MMMC Revenue Opportunity at Risk Due to Alternative Distribution Mechanisms (US$ millions) - Chart
• Exhibit 5.19: Exhibit 5.19: Traffic Breakup of MMMC Revenue Opportunity at Risk Due to Alternative Distribution Mechanisms (US$ millions) - Table
• Exhibit 5.20: Exhibit 5.20: Regional Estimated Revenues at Risk Due to Traffic Using Alternative Distribution Mechanisms (US$ millions) - Chart
• Exhibit 5.21: Exhibit 5.21: Regional Estimated Revenue Opportunity at Risk Due to Traffic Using Alternative Distribution Mechanisms (US$ millions) - Table
• Exhibit 5.22: Revenue Opportunity at Risk as a % of Total Multimedia Mobile Content Revenue Opportunity - Chart
• Exhibit 5.23: Estimated Revenue Opportunity at Risk as a % of Total MMCD Revenues - Table

• 6.1 New Opportunities and Strategies
  • 6.1.1 Mobile Network Operators
  • 6.1.2 Content Distributors
  • 6.1.3 Handset Manufacturers
  • 6.1.4 Content Owners and Publishers
  • 6.1.5 Advertisers