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Part 4: Future Directions

Part 4: Future Directions. Key Industry Trends . Fierce c ompetition from diverse industry players F ragmentation on multiple key technology areas Disruptive change of CDN video service and business model

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Part 4: Future Directions

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  1. Part 4: Future Directions

  2. Key Industry Trends • Fierce competition from diverse industry players • Fragmentation on multiple key technology areas • Disruptive change of CDN video service and business model • Availability of multiple sources of highly granular data and big data processing technologies • Higher consumer and business expectations on quality experience • Increasing role of cloud computing in Internet video

  3. Trend 1: Fierce Competition Among Diverse Categories of Industry Players • Emerging pure-play companies tries to dominate the new media • Netflix, Hulu, Youtube, Qiyi, Youku • Media companies exploiting new ways to engage consumers and monetize content • HBO, ESPN, NBC, CBS, Turner, Disney • CableTV, IPTV providers, and traditional aggregators strengthen their business • Verizon/RedBoxInstant, Comcast/Xfinity • Traditional and e-commerce retailers to include video • Amazon, Wal-Mart, Apple • Platform technology companies to become the new OTT cable operators • Intel, Microsoft, Google, Apple

  4. Trend 2: Fragmentation of Key Video Technology De-facto Standards • Flash was the de facto standard • Browser-based experience • Uniform development/user experience across diverse browsers and OSes • Four key functions: • rich interactive experience • video codec, player framework • streaming protocol • content protection • This world is dis-integrating with Microsoft, Google, Apple promoting alternative eco-systems

  5. The New Fragmented Eco-system • Interactivity: • Player framework: • Streaming protocol: • Content protection: HLS RTMP Progressive Download

  6. Content Publisher’s Perspective: Multi-device Requirements • Coverage: depending on content types • Live sports and movie streaming require the most device penetration (Netflix, Amazon Instant, ESPN, MLB, NFL are on 10s-100s of devices) • Quality: viewers demand high quality across all devices • Streamers across devices vary significantly in quality delivered • Quality requires significant investment per device • Analytics: comprehensive cross-platform important • Audience, quality, and content analytics in real-time • Content Protection: based on studio requirements • No cross-platform content protection exists today • Common: Encrypted HLS, REMPE, Tokenization, PlayReady/NDS/Widevine Adobe Access DRM

  7. Devices and Heterogeneity Growing Steadily

  8. High Quality on Emerging Platforms • Achieving high quality on emerging platforms will be more challenging than on PC • Closed systems and early stage software platforms • More network heterogeneity and variability with mobile • Higher quality/bit rate demands on TV • The drive towards high quality on emerging platforms will be more aggressive than on PC (2-3 years vs 10 years) • Premium content is being brought to devices at a rapid pace • Gap of quality is larger than on PC

  9. The Promise of HTML5 Video • HTML5 <video> tag is intended to be the standard interface to play and control video in browsers • HTML4 had generic object embed, not video specific • HTML5 video has been hindered by a lack of agreement on • Video formats and codecs • Content protection (encryption) • Streaming protocols • Ability to use adaptive streaming • Flash remains strong on PCs because of lack of standardization

  10. Current Status of HTML5 Video • Recent agreement in video and audio formats • MP4 for video (Firefox was last to adopt) • AAC, MP3 for audio • Recent extensions to HTML5 show a path to enabling adaptive streaming and content protection • Media Source Extensions enable adaptive streaming implementation in Javascript • Encrypted Media Extensions enable basic encryption and DRM • Browser support for extensions is not universal • Chrome is only browser with support today • IE and Firefox have announced support

  11. Next Steps in HTML5 Video • HTML5 video ecosystem must be built • Player frameworks • Adaptive streaming and high quality • Ad insertion • Content protection • Analytics • Closed captioning • Multiple language support • Timing is key • Transition from Flash to HTML5 in 2014 or later? • Focus of the industry is on apps and other devices • Ecosystem not ready for majority of publishers

  12. Trend 3: Disruption of CDN Video Business • Traditional video business model of Pure Play CDNs • premium pricing for premium service • one stop shopping for all services, globally • Key drivers for change • capital intensive business for streaming/bulk data services • streaming no longer commands premium pricing over bulk transfer, and unit prices for both are dropping … while at the same time … • rapidly expanding video services in viewership, global geography, higher bit rate, and longer form • increasingly higher expectation of customers and business on video service

  13. Trend: CDN Pricing CDN pricing has decreased x1.5-2 every year for the last 6 years

  14. Trend: Bitrate for Premium Content Kbps Average bitrate has increased 20-40% every year

  15. Trend: Per-hour Streaming Cost cents/hour Per-hour streaming cost has decreased 15-30% every year

  16. Unsustainable CDN Economics To Scale With Video Requirements • Video consumes 70% of Internet capacity today • 100x further growth needed by video … but scalability is hindered because of fundamental inefficiency in the video delivery chain • High network infrastructure and transit cost $ $ $ $ Does not grow with increased video traffic

  17. Emergence of Different CDN models controlling different part of eco-system • Traditional CDNs • Akamai, Limelight, Level 3, CDNetworks, ChinaCache • Controls only caches • Distributed vs. centralized architecture • Service Provider CDNs • Verizon, Comcast, British Telecom, Orange Telecom, ATT • Controls caches, switches, wires, subscription bills • Content Publisher CDNs • QQ, Qiyi, Google, Netflix • Controls contents, caches and end-to-end pipeline

  18. Different Systems Constraints For Various CDN Models

  19. ISP Participating Video Distribution • Cost reduction, additional revenue, better subscriber experience Cost reduction enables video growth without significant growth of ISP infrastructure

  20. Example Industry Initiatives • AkamaiAccelerated Network Partner Program • Akamai provides appliance for free • Akamai operates the CDN • Akamai services the appliance • ISP pays for bandwidth and power for the appliance • ISP gets cost benefit of caching within the network • NetflixOpenConnect • Netflix provides appliance for free • Netflix operates OpenConnect CDN • Netflix services appliance • Traffic to appliance goes through direct peering with Netflix • Akamai Aura Managed CDN and Licensed CDN • Akamai provides technology and optionally operational expertise to ISPs to operate their own CDN • These CDNs instantly become part of the Akamai Federation

  21. Trend 4: Multiple Sources of Granular Data and Big Data Processing Technologies • Fine grain data from multiple sources • Client side • available to content publishers, device manufacturers, device software platform providers • Server side • available to CDN providers • Within network • available to ISPs

  22. Trend 4: Big Data Processing Technologies and Application to Video • Big data technologies have improved significantly to allow sophisticated processing • Cost, scale, real-time • Both offline analysis and run-time optimization (e.g. control plane optimization in SIGCOMM’02) • Different industry players see different subsets of data and perform different analysis • Content publishers: with or without its own CDN • CDNs: pure play, provider-based, publisher-based • Consumer device and software platform vendors • ISPs and network equipment vendors

  23. Examples of Value Extraction From Data Analytics by Different Industry Players

  24. Trend 5: Growing Expectation on Quality Experience Business Value/Consumer Expectation Category Leader Premium UGV Quality 1% Increase in Buffering Ratio Reduces Engagement by 3 minutes in 2010 but 6 minutes in 2012

  25. Trend 6: Growing Importance of Cloud Processing in Internet Video • Cloud compute and storage key to end-to-end video pipeline • Dynamic scaling (e.g., large sporting events) • Enables publishers to deliver over the Internet with minimal infrastructure • Geographic reach without investment in physical infrastructure

  26. Cloud Computing in Internet Video Content preparation – Transcoding, packaging Origin storage, publishing to CDNs Ads – Server-side ad insertion to simplify client-side workflow complexity Video player – video player as a service hosted in the cloud to simplify content publisher workflows CMS / Metadata service Analytics Control-plane, coordination

  27. Wrapping Up • NOT all contents are the same • Video is fundamentally different from transaction traffic • We are at the very beginning of Internet video revolution • video is more than 60% Internet traffic today, will be more than 90% Internet traffic in 2-3 years • What is next? • Premium video on big screens  zero tolerance for poor quality: 4K + 3D video • Mobile video • Technical challenges • Quality, scalability, mobility, security, usability • Supporting diverse business models

  28. Opportunity for Research Communities • Internet video poses new challenges and impose new problem formulation on our traditional areas of interest • Quality, scalability, fault tolerance, security, network control, cross layer optimization, internetworking of different providers, interaction of technology and policy • New exciting adjacent technologies areas • Cloud computing • Big data processing • Software-Defined Networks

  29. Research Directions Discussed Earlier User plane: video Quality of Experience metric that captures user engagement Data plane: adaptive video control algorithm with web-compatible service access primitives (e.g. HTTP chunking) Control plane: coordinate control plane that performs network-wide optimization Many more …

  30. Example Research Questions on Cloud Computing and Internet Video • Video specific cloud infrastructures • Cloud and CDN integration • Geo distributed large data ingest and low latency response for analytics and control-plane cloud • Dynamic scaling algorithms based on load prediction • Real-time big-data processing as native features of cloud • Performance requirements • Time to publish content (especially important for news sites) • Time for player load globally • High concurrent viewers (live event) • Live transcoding latency • Availability and automatic failover

  31. One Example Video SDN Formulation • One entity (SDN controller) controlling end user devices, encoders, origin servers, CDN servers, and network elements • How much could quality be improved? • How much could efficiency/cost of infrastructure be improved? • What are the most valuable data sources? • Does dynamic controlling of encoded bit rates at the encoder help improve quality or is the static multi-bitrate good enough?

  32. Improving CDN Performance with Additional Data • How much improvement in quality and efficiency can be gained by incorporating viewer experience measurements into the server selection decision? • How much improvement in quality and efficiency can be gained by content aware server selection? • Content popularity, viewing patterns, etc.

  33. The Return of P2P • The future video delivery is a combination of • CDN • Service provider CDN • Cloud providers • Peer-assisted delivery • New problem formulations and challenges • Control scope is not just a single group or content, but across an entire business entity (e.g. all video served by HBO, Netflix, Youtube) • Multiple policy considerations between different industry players • Control stability within entity and across entities • Security challenges (including resource attacks)

  34. Improving HTTP Streaming Protocols • Protocols need to be optimized and customized for different environments • Cellular 3G • Cellular 4G • Cable internet access • DSL internet access • FiOS • Service provider specifics • Range of bit rates (low end range for phones vs high end range for TV screens) • How much should the algorithm know about the network structure (i.e., cable network architecture)?

  35. Cross Device and Publisher Caching • Different devices use different HTTP chunking formats (HLS, HDS, SmoothStreaming, DASH) • Different content publishers have different copies of the same content • For example, consumers can access the latest episode of Game of Thrones on HBO GO, Xfinity On Demand, AT&T Uverse On Demand, iTunes, etc. • How can cross-device and cross-publisher caching be enabled? • What is the efficiency / cost savings benefits of doing this? • What are the data-plane and control-plane requirements to do this?

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