Sky Italia - Operation Evolution - London - March 20th, 2018 - Connected TV World Summit
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Sky Italia - Operation Evolution
London – March 20th, 2018
1
Sky Italy to IP-based distribution
Content Contribution Core Network Access Network Home Content Display
Transmission Network (FTTx) Network
Public Internet /
Global CDNs
Managed CDN
Headend
Headend
Managed CDN
Private CDN
Headend
2
Manage the entropy of IP
CDN Selector
BI Daily Realtime
Logs Macro Alerts Conviva
CRM
Tech Reporting
Off-line Telemetry Real–time Tracking Beacon
CDN Logs Intelligence Logs
1 minutes hearbeat
Distributed over 2
datacenters and 2
public clouds
4 catalaogues made
Original Personalized
with 3 streaming
protocols and 3 Manifest Manipulated Manifest
DRMS CDN SELECTOR
Encoding superset
of bitrates for
linear, VOD and Origin Client
D&P Content Content
Server devices
Chunks Chunks
CDNs
7 CDNs: ISP local,
global and private
4
Define a QoS
vQoS and Sky Service Priority
• Provide high quality experience during
multiple event of live-vod streaming + 1
or more concurrent streaming events.
Lower priority services are limited via:
• Simulation of network QoS experience
• Throttling of stream delivery on edge
server
• Midstream switching between same
service/different capped bandwidth
FQDN, based on telemetry information
• Collection of real time concurrent
activity via telemetria
• Priority list: VOD/Linear streaming, OTT
streaming, Recording/D&P
6vQoS and Sky Service Priority 7
Improve the CDN distribution capabilities
New CDN Ranking and Allocation Logic
High-Level Functioning of the Algorithm
The current prototype algorithm routes a given IP aggregation at given time following 3 main steps. Input variables to the algorithm
can be weighed as wished.
1 2 3
Quality of Service QoS-driven QoS-driven
Index CDN ranking allocation
Bitrate
Number
of
errors
Rebuffering
events & time
The output of the algorithm for a given IP aggregation (in this case IP /20) and time instance is the following table reporting the
fundamental results of the calculations.
CDN # SSTT Events QoS Index Final Allocation
CDN 1 22 0.6630 25.64%
CDN 2 18 0.5549 21.46%
CDN 3 46 0.5345 20.67%
CDN 4 1 0.4000 15.47%
CDN 5 73 0.2187 8.46%
CDN 6 0 NA 8.30%
10Cloud Scalability
Video Encoding Workflow as it was
‘Standard
’ VOD (on STB, Box sets, Kid Apps, Sky Go, Nowtv)
on- Transcoding Multiplexing Packaging Encryption Distribution CDNs
premise
VOD
solution
• Persistent File • Persistent Clear • Temporary Clear • OTT Catalogue
Content • 8-15Mb/s Cache Packaged Cache • HLS, HSS, Dash,
Ingest • 1080i H264 • Multi bitrate mp4 • HLS, HSS, Dash, TS
Content Master File • mp4 @8-15 Mb/s • 1080p up to 5Mb/s TS • 1080p up to 5Mb/s
• 50Mb/s • 1080p up to 5Mb/s
• High Resolution/
MPEG2
12Video Encoding Workflow Evolution
‘Standard’
cloud Cloud platforms
• Sky Technology DC
VOD Transcodin
• Amazon Web Service
g • Google Cloud Engine
solution
‘Standard’ VOD (on STB, Box sets, Kid Apps, Sky Go,
on- Transcodin Multiplexin
NowTV)
Packaging Encryption Distribution CDNs
premise g g
VOD
solution
Content
Ingest
• Persistent Clear Cache • Temporary Clear • OTT Catalogue
Content Master File • Multi bitrate mp4 Packaged Cache • HLS, HSS, Dash, TS
• 50Mb/s • 1080p up to 5Mb/s • HLS, HSS, Dash, TS• 1080p up to 5Mb/s
• High Resolution/ MPEG2 • 1080p up to 5Mb/s
13Video Encoding Workflow: Sky Italia Solution
Sky Italia VOD
Hybrid solution
can reduce the
2nd Step Cloud platforms
lead time for Transcodin • Red Hat Openshift
delivering VOD g • Public Cloud
Providers
assets while
keeping high VOD (on STB, Box sets, Kid Apps, Sky Go,
signal quality 1st Step
Nowtv)
Transcodin Multiplexing Packaging Encryption Distribution
without g
increasing costs
Content
Ingest
• Persistent File • Persistent Clear • Temporary Clear • OTT Catalogue
Content Master File
• 8-15Mb/s Cache Packaged Cache • HLS, HSS, Dash,
• 50Mb/s
• 1080i H264 • Multi bitrate mp4 • HLS, HSS, Dash, TS
• High Resolution/
• mp4 @8-15 • 1080p up to 5Mb/s TS • 1080p up to
MPEG2
Mb/s • 1080p up to 5Mb/s
5Mb/s
14Low Latency
Low Latency
• A self developed origin server threats
the streaming signal to be served with a
minimal delay to live
• It works with any standard players
• Processing: http://lowdelay.sicdn.it/getFile/
• 2 chunks look-ahead manifest 217851/tg24/index.m3u8?align
• 2s chunks =always
• Serve-before-close file delivery
• All clients aligned to the same chunk
• More aggressive processing and latency
could be reached with dedicated players
16Video Artificial Intelligent
Binge Watching
To detect the opening and closing
credits in a video and also
discriminates non interesting Next Episode in 5
S1: E 12 “Two
credits from storytelling credits Swords”
PLAY
which are slightly different from
episode to episode and are
considered part of the show by
viewers.
Episode 11 Episode 12
18
Thanks to video analytics is possible to extract moreVideo Content Recognition
FACE NUDE METADATA VIDEO
RECOGNITION DETECTION EXTRACTION ANALYSIS
Applying objects
Artificial Intelligence recognition
Algorithms may be
technology can be used functionalities to videos,
AI technology can be defined and used to train
to add celebrity it’s possible to detect
applied to analyze Sky AI systems starting from
tagging and face and tag particular types
videoclips (or coming human / subjective
detection capabilities to of scenes based on
from 3rd parties), to evaluations and
existing systems, in specific objects they
automatically detect categorizations, aiming
order to let the may contain (e.g.,
those with inappropriate to assess “how much” a
automatic recognition of «violent» sequences
content containing nude video can be classified
celebrities during the may be detected in a
scenes, to be discarded as “violent”, or “comic”,
playback of usual video movie, when «shoots»
/ censored. or belonging to other
contents of the or «blood» are
categories.
distribution pipeline. recognized in those
scenes)
VIDEO CONTENT RECOGNITION APPLICATIONS
1920
Quality Optimization
Optimization @Constant Optimization @Constant Quality
Bitrate Constan Constan • Objective: optimizing the
t t
• Objective: maximizing the Bitrate Quality quality/bitrate ratio. Providing a
perceptual quality, Approac Approac controlled quality in content-
maintaining the classical h h aware VBR to reduce costs and
constraints of CBR encoding optimize QoE
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