SIGCOMM’2013 Tutorial: Hui Zhang 1.Fierce competition from diverse industry players 2.Fragmentation on multiple key technology areas 3.Disruptive change of CDN video service and business model 4.Availability of multiple sources of highly granular data and big data processing technologies 5.Higher consumer and business expectations on quality experience 6.Increasing role of cloud computing in Internet video Key Industry Trends
SIGCOMM’2013 Tutorial: Hui Zhang 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
SIGCOMM’2013 Tutorial: Hui Zhang 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: 1. rich interactive experience 2. video codec, player framework 3. streaming protocol 4. content protection This world is dis-integrating with Microsoft, Google, Apple promoting alternative eco-systems
SIGCOMM’2013 Tutorial: Hui Zhang The New Fragmented Eco-system Interactivity: Player framework: Streaming protocol: Content protection: RTMP HLS Progressive Download
SIGCOMM’2013 Tutorial: Hui Zhang 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
SIGCOMM’2013 Tutorial: Hui Zhang 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
SIGCOMM’2013 Tutorial: Hui Zhang The Promise of HTML5 Video HTML5 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
SIGCOMM’2013 Tutorial: Hui Zhang 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
SIGCOMM’2013 Tutorial: Hui Zhang 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
SIGCOMM’2013 Tutorial: Hui Zhang Trend: CDN Pricing CDN pricing has decreased x1.5-2 every year for the last 6 years
SIGCOMM’2013 Tutorial: Hui Zhang Trend: Bitrate for Premium Content Average bitrate has increased 20-40% every year Kbps
SIGCOMM’2013 Tutorial: Hui Zhang Trend: Per-hour Streaming Cost Per-hour streaming cost has decreased 15-30% every year cents/hour
SIGCOMM’2013 Tutorial: Hui Zhang 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 Content PublisherCDN ProviderISPConsumer Traditional CDN Model Pays CDN provider Pays for servers Pays for transit Pays for network infrastructure Pays for transit Pays ISP Pays Content Publisher $ $ $$ Does not grow with increased video traffic
SIGCOMM’2013 Tutorial: Hui Zhang 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
SIGCOMM’2013 Tutorial: Hui Zhang Different Systems Constraints For Various CDN Models Traditional CDNService Provider CDN Content Publisher CDN Multiple data sources Server selection based on multiple data sources: viewer (quality), server (load), network (load/congestion) Server placementPlacement with respect to switches. Integration with switches CachingCaching close to the consumer vs cache performance Caching optimized based on knowledge of content Pre-populated caches vs proxy caches vs hybrid: Pre-population for new popular content before content is available based on historical knowledge. Latest Game of Thrones episode viewer patterns can be predicted based on history Control and coordination Control-plane to optimize across CDNs and CDN types. Content aware and audience aware control protocols Data-planeData-plane protocols to seed CDNs with content
SIGCOMM’2013 Tutorial: Hui Zhang ISP Participating Video Distribution Content Publisher CDN ProviderISPConsumer Traditional CDN Model Pays CDN provider Pays for servers Pays for transit Pays for network infrastructure Pays for transit Pays ISP Pays Content Publisher CDN Exchange Pays CDN provider Reduced transit cost Reduced infrastructure cost Reduced transit cost Pays ISP Pays Content Publisher Cost reduction, additional revenue, better subscriber experience Cost reduction enables video growth without significant growth of ISP infrastructure
SIGCOMM’2013 Tutorial: Hui Zhang Example Industry Initiatives Akamai Accelerated 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 Netflix OpenConnect 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
SIGCOMM’2013 Tutorial: Hui Zhang 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
SIGCOMM’2013 Tutorial: Hui Zhang 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
SIGCOMM’2013 Tutorial: Hui Zhang Examples of Value Extraction From Data Analytics by Different Industry Players Device platform OwnersCDN Equipment Vendors Cross-publisher, cross-CDN performance visibility Cross-CDN performance visibility with deep network and server-side statistics Feedback to publishers on device optimization, comparisons / benchmerks Feedback to CDN operators on deployment and operation Understand device specific usage patterns and feedback to navigation system Server selection based on real-time cross-CDN load/performance information Caching optimization based on device- specific usage patterns CDN performance comparisons / benchmarks
SIGCOMM’2013 Tutorial: Hui Zhang - Conviva Confidential - Quality Business Value/Consumer Expectation UGV Premium Category Leader Trend 5: Growing Expectation on Quality Experience 1% Increase in Buffering Ratio Reduces Engagement by 3 minutes in 2010 but 6 minutes in 2012
SIGCOMM’2013 Tutorial: Hui Zhang 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
SIGCOMM’2013 Tutorial: Hui Zhang 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
SIGCOMM’2013 Tutorial: Hui Zhang 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
SIGCOMM’2013 Tutorial: Hui Zhang 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
SIGCOMM’2013 Tutorial: Hui Zhang 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 …
SIGCOMM’2013 Tutorial: Hui Zhang 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
SIGCOMM’2013 Tutorial: Hui Zhang 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?
SIGCOMM’2013 Tutorial: Hui Zhang 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.
SIGCOMM’2013 Tutorial: Hui Zhang 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)
SIGCOMM’2013 Tutorial: Hui Zhang 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)?
SIGCOMM’2013 Tutorial: Hui Zhang 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?