SET Expo Nova TV por Assinatura. A Tecnologia por traz da Harmonic Inc. All rights reserved worldwide.

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1 SET Expo 2017 A Tecnologia por traz da Nova TV por Assinatura

2 SET Expo 2017 Introduction 2

3 TV world is changing Apparition of pure players Global actors with important investment Fast web-oriented innovation Netflix first, but lots of developments since last year New TV consumption schemes Timeshift, or event-based catalog has become main stream ( anytime ) Address new video devices on any network ( anywhere ) TV operators can match these And do more - Leverage the existing subscribers base - Already have the content rights, especially on linear and local - Already have a device in users living room - can aggregate the service (content and billing) A lot have started already 3

4 TV OTT streaming still increasing Source: Global OTT TV & Video Forecasts

5 Traditional delivery using Broadcast/Multicast Same content for all, pushed to the end devices Continuous stream to the network Single bit-rate and resolution Dedicated network with guaranteed QoS for the selected bitrate Bitrat e (kbps) Time 5 5

6 Multiscreen delivery using Adaptive Streaming Unicast, content is requested by each device, potentially a different stream per user Various bit-rate and resolution that the player can chose from Uses existing HTTP distribution network (private or public = OTT ) Bitrate (kbps) Time 6 6

7 Legacy: OTT Live streaming and VOD Live Broadcast Transcoder Broadcast remains separated Live/File Live OTT OTT Transcoder Transcoder Packager Origin Server DRM Server VOD Storage Same model as traditional Broadcast applied to mobile devices 8

8 Today: Timeshift & 1 st Screen Live Broadcast Transcoder Convergent Broadcast & OTT Transcoder Live/File Live OTT OTT Transcoder Transcoder Packager Origin Server DRM Server VOD+LIVE Storage 1- Enable Timeshift on Live channels (StartOver, Catchup, ndvr, trick play ) 2- Convergent system & OTT Timeshift for 1 st screen 3- Possibly, OTT Live for 1 st screen as well 9

9 SET Expo 2017 Managing Content in the past 10

10 Timeshift viewing adoption example Summary: Live ~55% StartOver/Catchup ~35% VOD/PVR ~10% Growing tendency for Timeshift vs Live 11

11 Start-Over Customer experience The ability to skip to the beginning of a currently airing program Easy to use Restart program Easy content rights Easy advertising model Low cost implementation on both clients and server sides 12

12 Catch-up - Consumer experience The ability to watch a program that has ended Two representations examples 1. Retro-EPG 2. Catchup Portal More elaborate/advanced user interface Higher cost of system (storage) Content rights (<3 days vs. > 3 days) Program available for 1 week Straightforward server side implementation 13

13 Cloud DVR and VOD Customer Experience Programs are de-linearized Two representations examples Personal Video Recordings Operator Recordings / VOD library Advanced Timeshift user experience Ad hoc recording Season ticket, download to go/own Higher cost of system (but much less than HDD!) Challenging content rights 14

14 Origin server: managing content in the past Library storage Circular Buffer Player Buffer Now Past LIVE stream Future T2 T1 T0 = Now Circular Buffer Player buffer: limited (few minutes max), depends on device = not reliable Circular buffer: All channels recorded all the time for N days Extraction and copy: Only selected assets are kept after N days LIVE skip-back Start-over Catch-up ndvr / Lasting Catch-up 15 15

15 Catch-up Play from the buffer Segments of programs are referenced by a playlist/manifest and identified by a timestamp DRM CMS Live Electra ProMedia Origin CDN Client Channel time-shift buffer MediaGrid Previous Previous Program Program 2-2 Previous Program 1 Current Program VOD like Playlists T3 T2 T1 T0 Live Start-Over Catch-Up 16

16 Live to VOD workflow VOD assets copy from cached material DRM CMS Live LLCU T1 T2 LLCU T2 T3 Electra ProMedia Origin CDN Client Channel time-shift buffer MediaGrid Previous Program Previous Program Current 2 1 Program VOD Playlists T3 Long Lasting assets T2 T1 T0 Live Start-Over Catch-Up 17

17 Why is circular buffer mandatory? Circular Buffer: Why is it mandatory? because past events need to be available right away! 1- To allow StartOver and Rewind 2- Popularity of an event decreases exponentially with time: 2h latency = Already ~10% of users frustrated -> no time to program a record and wait for the end of the ingest) 18

18 Packaging On The Fly (POTF) DRM ProMedia Package-Origin CMS Live Transcoder Packager Origin CDN Client MediaGrid Common Format Advantages Storage cost savings Future proof packaging technology Challenges Eco-system adjustments Scaling DRM, CMS 19

19 SET Expo 2017 Optimizing Delivery 20

20 Streaming formats getting clearer x DRM systems x formats versions Playready initial DRM #1, DRM #2, etc PlayReady w/ key rotation Version X, Version Y, etc... Playready scalable licenses Access Encoding.com 2016 format report Encoding.com 2017 format report 21

21 DASH + HTML5 Chrome, Firefox, Edge Browsers don t support plugins anymore, including Silverlight HTML 5 extensions MSE (Media Source ext.): generates media streams for playback EME (Encrypted Media ext): interface for encryption DASH + HTML extensions pretty much supported on all browsers Source: Bitmovin.com, Feb 2015 Used by Netflix & Youtube 22

22 DRM devices support (May 2016) 3 formats cover all: Playready, Widevine, Fairplay EME Content Decryption Module replaces the secure player (but comes free!) In theory, there could be several CDM Practically, mainly only the CDM of the browser (Chrome -> Widevine, IE -> Playready, ios -> Fairplay) 23

23 DASH CENC overview ISO standard Only specifies the format of the encrypted packet, not the DRM system Enables decryption of the same file by different DRM systems Compatible in particular with PlayReady, FairPlay, Widevine Based on PIFF (1.3) / ISOBMFF /MP4, very similar to PlayReady Licenses Servers Moov PSSH PlayReady FairPlay Widevine Moof encrypted packet Video Audio PlayReady FairPlay Widevine AES CTR or CBC, supports sample-based encryption 24

24 CMAF: Packaging convergence MPEG Common Media Application Format (CMAF) ISO standard (Apple, MSFT, Google, Akamai,...) planned for end Draft already available Goal: Same video packets for both formats (which represents most of the traffic on network/storage), only the playlist/manifest is different. Essentially based on ISOBMFF, DASH and CENC (ie ~DASH) Additional targets: lower latency, Ad insertion, storage, broadcast & PDL HLS Manifest TS CMAF CDN fmp4 DASH Manifest 25

25 Addressing latency with HTTP Chunked Transfer Any delivery segment can be delivered using HTTP Chunked Transfer Coding segment 1.mp4 Data Data Data Data Size: bytes data... Size: bytes data... Size: bytes data... Size: bytes data... 26

26 Segments Building and Transfer Workflows Legacy HLS or DASH Segments Flow Encoder/Packager Origin: 1 Live segment Player: 2x or 3x segments 6s segment N Segment N-1 Segment N-2 Segment N-3Segment N-4 Start decoding CMAF Chunks + HTTP Chunks Flow Encoder/Packager Chunk(200ms) Segment N Live Origin: 1 chunk 2s Delivery segment is split into 200ms CMAF chunks being delivered using HTTP Chunked Transfer Coding Player: 1x segment Segment N-1 Start decoding 27

27 Multi Master playlist: deterministic profile selection 5 Mbps Master playlist 2 Mbps 1 Mbps 5 Mbps TV playlist 0.5 Mbps (Unbearable quality on a big screen) 2 Mbps 1 Mbps 0.5 Mbps Cell playlist 5 Mbps 2 Mbps (high BR costs for no visible quality improvement) 1 Mbps 0.5 Mbps 28

28 Hit rate and Cache size optimization Hit rate = 80% Hit rate = 90% CDN cache Hit rate greatly improved by adding cache capacity up to a certain point CDN cache is easily below the flat part of the curve CAUTION: Cache size for a given hit rate depends on the size of each asset Number of packages counts Compression efficiency counts 29

29 Codec evolution H264 Ubiquitous WebM(VP8/VP9) HTML5, YouTube, mainly free content +4% HEVC Slowed down by license pool split MPEG-LA; HEVC Advance; Velos media Encoding.com 2016 format report AOM - AV1 Browsers Royalty free Hardware decode? Interop? Performance, patent infringement? MPEG JVET (~2020) 30

30 bitrate Traditional ABR Compression: Constant Bitrate Classical ABR solutions rely on CBR encoding for each profile Most sequences use a lot less bits Video quality is not consistent Simple Video = Wasting Many Bits Simple Video = Wasting Many Bits Complex Video Complex Video Complex Video Moderate Complexity = Wasting Some Bits Moderate Complexity = Wasting Some Bits 3.5 Mbps CBR 2.0 Mbps EyeQ.63 Mbps * 2 sec =.16MB.63 Mbps * 2 sec =.16MB 4.3 Mbps * 2 sec = 1.08MB 5.0 Mbps * 2 sec = 1.26 MB 4.2 Mbps * 2 sec = 1.06 MB 2.2 Mbps * 2 sec =.56 MB 1.9 Mbps * 2 sec =.48 MB 31

31 bitrate Improving existing standards Real-time analysis to use only the bits needed to achieve the desired video quality Constant video quality per profile rather than constant bitrate Achieving a more consistent experience using less bandwidth Shows over 30% savings in bandwidth required (huge network and storage savings) Less bandwidth also means less buffering (#1 QoE issue reported by users) Still compatible with H264 and H265 formats Simple Video = No wasted bits Simple Video = No wasted bits Complex Video = Capped Complex Video = Capped Complex Video = Capped Moderate Complexity = No wasted bits Moderate Complexity = No wasted bits 3.5Mbps 2.0Mps.63 Mbps * 2 sec =.16MB.63 Mbps * 2 sec =.16MB 3.5Mbps * 2 sec =.88MB 3.5Mbps * 2 sec =.88MB 3.5Mbps * 2 sec =.88MB 2.2 Mbps * 2 sec =.56 MB 1.9 Mbps * 2 sec =.48 MB 32

32 SET Expo 2017 Agile infrastructure: Virtualization & Cloud 33

33 What are the main reasons? Appliance based challenges Appliance & connectivity are often provider and application specific Complex & inflexible Long cycles for new architectures or expansion High infrastructure OPEX Moving to IT standards Standard HW which can be used for any purpose Abstracts the infrastructure complexity Puts in common infrastructure OPEX Agile, a new system can be set up in weeks, a new service in hours Auto-scaling, Elasticity, Orchestration Cloud services 34

34 Change of mindset Unique Identical 35

35 SW on COTS Blade Server Advantages Implies that all video products run on SW Why standard servers? Choose HW platform irrespective of video vendor / application Prefered House platform Better price, local supply Simplified redundancy, sparing, purchasing Why blades? Easier physical installation Savings on networking Ports / cables / wiring / cooling&power / space Network complexity is hidden inside blade fabric 36

36 Virtualization control layer Virtualization layer on top of the HW -> Abstracts the difference between server models Allows several Virtual Machines per host, possibly running different OS types Easy VM imaging and replication Network switching and storage are included into the virtualization layer Centralized infrastructure management 37

37 A Tale of Two Clouds CLOUD VIRTUALIZATION 38

38 Cloud Computing Definition (NIST) Characteristics On-demand self-service Resource pooling Rapid elasticity Measured service Broad network access Service Models Infrastructure as a Service (IaaS) Platform as a Service (PaaS) Software as a Service (SaaS) 39

39 Cloud Models 40

40 Different Types of Cloud Deployment Models 41

41 Public clouds Amazon Web Services Microsoft Azure Google cloud 42

42 Private Cloud Infrastructure What is Private Cloud? Building your own on-premise secured cloud Private Cloud OS MSFT Hyper-V Citrix XenServer OpenStack Private Cloud (VMWare vcloud) 43

43 Example of Private-Public cloud mix: DR Architecture Private cloud CloudLink On-Premises Back Office Config data / Backup CMS DRM Dynamic Ad-Insertion Blackout Open internet CloudLink Direct link Public cloud 44

44 ETSI NFV 45

45 SDN: Software Defined Networking What is SDN? Centralize the control plane, distributed elements are not configured but provisioned from the SDN controller SDN switches are all equivalent, no need for specific features 46

46 Micro-services 47

47 VM vs containers A VM is self-contained while a container relies on the OS Kernel -> lighter structure Same idea but containers are typically: Segmented into smaller pieces One container per elementary function More dynamic and suited for orchestration VM can be used to group containers VM Question: How to chain containers together into a system? 48

48 Infrastructure vs processes management Management type Infrastructure Processes HW resources Organize in pools Use HW pools Images installation based on available resources based on image reserved resource based on available resources based on image reserved resource based on application needs Auto-scale adds/removes servers/images adds/removes processes Network management Image level Process level Redundancy Image level Process level 49

49 Processes Orchestration Next-generation System Management Infrastructure Orchestration Provisioning 50

50 What does virtualization practically brings me? - Outsources the configuration, operation and supervision The system automatically installs and scales its components - no need for dimensioning each function individually - common and automated environment deployment - OS and SW installation easy management or even automated - Resources (CPU, RAM, network) mutualized, all servers are equivalent - Less racking, wiring, networking - Efficient centralized interface 51

51 New NFV-driven Video Architecture Ingest Playout Graphics Transcode Encrypt Deliver Process Orchestration and Provisioning Dedicated Servers Virtualized Cloud Service Products are no longer separated boxes but a SW micro-services Adaptable to any environments, in particular Cloud (but also traditional self-contained box) System management = standard process orchestration + video service provisioning 52

52 SET Expo 2017 Monetizing with Advertisement 53

53 Global TV Advertising Revenues 2 big advantages on Web: Targeted Ads Impression feedbacks Global Internet advertising surpassed TV advertising in 2016 TV advertising still growing, but decreases in average Ad value. 54

54 OTT Advertising vs traditional broadcast Simpler insertion OTT streaming is based on a Playlist/Manifest listing all the program segments to be played one after the other The Ad is not physically spliced into the stream, only the URL reference to the Ad is added in the list As many different playlists/manifests as necessary can be customized Works for targeted Ads In case of different Ads per user, only the reference to the Ad differs, the rest of the playlist remains the same for all users No need to duplicate the whole stream to make different Ad variants Fully addressable by playlist structure and unicast nature Geographic ad zone matching Household addressable Device / Person addressable 2-way http communication Robust Interactivity potential Measurement & reporting Same advantages as web Simpler and cheaper than traditional solution Also addresses Live streams 55

55 Ad Insertion into ABR Live Streams Ad signal Conditioning Playlist Annotation Network Feed Transcoder Output Fragmenter Output SCTE 35 Program Default Ad Program IDR IDR IDR IDR IDR IDR IDR IDR IDR 1 2 CUE-OUT 3 ad ad AVAIL ad ad ad CUE-IN Playlist Annotation/decoration Playlist Manipulation Client #1 Local ad #1 Local ad #1 Local ad #1 Local ad #1 Client #2 Local ad #2 Local ad #2 Local ad #2 Local ad #2 Playlist Customization 56

56 Network vs Client-based architectures 57

57 Ad Annotations Playlist annotations are special tags written in the HLS playlist or DASH Manifest Client-side: the client reads these annotations and performs ad insertion. Server-side: A playlist manipulator can then utilize these tags to know when events start/end and replace the corresponding segments with alternate content Ex: (SCTE-35 standard) 59

58 Alternative to SCTE-35/104 in the source Signaling present in the source SCTE-35 messages if MPEG-TS input or SCTE-104 if SDI Possibly with ESAM POIS validation Scheduling: Ad insertion can be programmed in a schedule SCTE-104 IP ESAM interface Ad detection systems 60

59 Insertions are not only for Ads Local Content Slate Insertion Rights management Emergency alerts More can be imagined Same technical workflow 61

60 SET Expo 2017 Conclusion 62

61 OTT/Web Pros and Cons: Where do we stand? Yesterday s Today perception PROS Individualized experience (VOD, cdvr, Ads, regional content, individualized content, ) Managing content in the past ( Anytime : StartOver, Trick Play, Catchup, VOD, cloud DVR,, ) Ubiquitous http distribution ( Anywhere : all devices rented/user s, any network public/private, ) Uses standard technologies and infrastructure (datacenters/cloud, Web infrastructure, retail devices, ) Strong analytics (content watched, user s profiling, ) CONS Uncontrolled unicast traffic on the network Latency Complex transition: new system/operation Moving technologies: make right choices? better compression and CDN/network, common format, CMAF low latency versatile solutions: boxes/cloud, broadcast/ott Consolidation DASH/HLS, Ad insertion, 63

62 Conclusion New models of TV consumption inspired by the Web model Need to fight with the same weapons: o Product natively anytime, anywhere, go beyond usual linear models o Agile and performant infrastructure o Reclaim advertisement revenue by matching and beating the Web offer How to get there? o Revolution the mode of operation is the fastest but also dangerous for existing business o Safer to have a solution adaptable to both current and future targeted operations Adding features progressively as they are needed Migrating the infrastructure step-by-step, at a safe pace 64

63 Questions and Answers 65