Part 4: Future Directions

SIGCOMM’2013 Tutorial: Hui Zhang- Conviva Confidential -

Part 4: Future Directions

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 model4. 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


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


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 framework3. streaming protocol4. content protection

• This world is dis-integrating with Microsoft, Google, Apple promoting alternative eco-systems


The New Fragmented Eco-system

• Interactivity:

• Player framework:

• Streaming protocol:

• Content protection:

RTMP HLSProgressiveDownload


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


Devices and Heterogeneity Growing SteadilyScreen Devices Video Platform Programming

LanguagePC Screen PC / Mac Flash in browser ActionScript

Silverlight in browser

C#

HTML5 in browser JavascriptPhone / Tablet Screen

iPhone/iPad/iPod/AppleTV

Native application Objective-C

HTML5 in browser JavascriptAndroid Phones/GoogleTV

Video View (native player)

Java

Flash/AIR (deprecated)

ActionScript

HTML5 in browser JavascriptNexStreaming JavaVisualOn Java… …

Windows Phone Silverlight C#TV Screen Xbox 360 Native C++ + Lua

Lakeview (Silverlight)

C#

PS3 Native C++Trilithium / Web MAF Javascript

Roku Native BrightscriptSamsung Smart TV

Native Javascript

Apple TV Native Javascript

Other TVs: LG TV, Sony TV, Panasonic TV, Vizio TV

Streaming players: YouView STB, Nagra,

New devices: Xbox One, PS4, Chromecast


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


The Promise of HTML5 VideoHTML5 <video> tag is intended to be the

standard interface to play and control video in browsers HTML4 had generic object embed, not video

specificHTML5 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


Current Status of HTML5 VideoRecent 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 DRMBrowser support for extensions is not

universal Chrome is only browser with support today IE and Firefox have announced support


Next Steps in HTML5 VideoHTML5 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


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


Trend: CDN Pricing

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

2006 2007 2008 2009 2010 201105

1015202530354045

cent

s/G

B


Trend: Bitrate for Premium ContentAverage bitrate has increased 20-40% every year

2006 2007 2008 2009 2010 20110

200400600800

10001200140016001800

Kbps


Trend: Per-hour Streaming CostPer-hour streaming cost has decreased 15-30% every year

2006 2007 2008 2009 2010 20110123456789

10

cent

s/ho

ur


Unsustainable CDN Economics To Scale With Video Requirements Video consumes 70% of Internet capacity

today100x 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 Publisher

CDN Provider

ISP Consumer

Traditional CDN Model

• Pays CDN provider

• Pays for servers

• Pays for transit

• Pays for network infrastructure


• Pays ISP• Pays

Content Publisher

$ $

$$ Does not grow with increased video traffic


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


Different Systems Constraints For Various CDN Models

Traditional CDN Service Provider CDN

Content Publisher CDN

Multiple data sources

Server selection based on multiple data sources: viewer (quality), server (load), network (load/congestion)

Server placement

Placement with respect to switches. Integration with switches

Caching Caching 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-plane Data-plane protocols to seed CDNs with content


ISP Participating Video Distribution

Content Publisher

CDN Provider

ISP Consumer

Traditional CDN Model


• Pays for servers


• Pays for network infrastructure



Content Publisher

CDN Exchange


• Reduced transit cost

• Reduced infrastructure cost

• Reduced transit cost


Content Publisher

Cost reduction, additional revenue, better subscriber experience

Cost reduction enables video growth without significant growth of ISP infrastructure


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


Trend 4: Multiple Sources of Granular Data and Big Data Processing Technologies Fine grain data from multiple sourcesClient side

available to content publishers, device manufacturers, device software platform providers

Server side available to CDN providers

Within network available to ISPs


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


Examples of Value Extraction From Data Analytics by Different Industry Players

Device platform Owners CDN Equipment VendorsCross-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


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


Cloud Computing in Internet Video Content preparation – Transcoding,

packagingOrigin storage, publishing to CDNsAds – Server-side ad insertion to simplify

client-side workflow complexityVideo player – video player as a service

hosted in the cloud to simplify content publisher workflows

CMS / Metadata serviceAnalytics Control-plane, coordination


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


Opportunity for Research CommunitiesInternet 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


Research Directions Discussed Earlier User plane: video Quality of Experience

metric that captures user engagementData 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 …


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


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?


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.


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)


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)?


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?

Documents

Part 4: Future Directions