Digital Media Production

Digital Media Prodution
Background, challenges and Opportunities

Table of Content
2004 – Background and Objectives
2009 – Due Diligence
State of the technology
Reconciliation of requirements
Objectives and Challenges
Operational Excellence
Scale up
Media Asset Management
Additional requirements
Broadband distribution
Supply chain integration
Technology trends

2004...

Background – Proof of Concept

5
4/8 KB segment
Spindle
Arm
Arm pivot
Sector
Platters
Cylinder
Arm assembly
Tracks
Heads
128 KB segment
100+ HD’s
// Striping:

Large segment size-> Higher efficiency Hard Disk

Media File
Media File
Media File
Media File

Fully fragmented: Random access without using any Hard Disk intelligence

Hard Disk Model

6
4/8 KB segment
Spindle
Arm
Arm pivot
Sector
Platters
Random R/W
8KB – 128 KB Segments
Random
8 KB segments
Random
128 KB segments
Cylinder
Arm assembly
Tracks
Heads
128 KB segment
R/W on the Outer Track
Full Stroke R/W
8KB – 128 KB Segments
Outer track
Full stroke
8 KB segments
Full stroke
128 KB segments
Inner track
R/W on the Inner Track

Large segment size-> Higher efficiency Hard Disk

Hard Disk Model

7
Hard Disk Speed
Disk
Throughput
15 Krpm calculated results
10 Krpm calculated results
128 KB segments
8 KB segments
Testresults
78.2 MB/s
72.9 MB/s
71.5 MB/s
70 MB/s
66.7 MB/s
=> 10 MB/s(SCSI/FC HD)
(6.6MB/s for (S)ATA disk)
50 MB/s
50.9 MB/s
47.6 MB/s
39.4 MB/s
35.4 MB/s
30 MB/s
16.8 MB/s
14.8 MB/s
12.8 MB/s
12.2 MB/s
10 MB/s
9.1 MB/s
8.9 MB/s
0.91 MB/s
0.65 MB/s
0.92 MB/s
0.62 MB/s
15Krpm – 10 K rpm
15Krpm – 10 K rpm
15Krpm – 10 K rpm
15Krpm – 10 K rpm
Read load types
(1)
Sequential Read
Outer tracks
(2)
Sequential Read
Inner tracks
(3)
Random Read
Tot. Fragmented disk
128 KB / 8KB segments
(4)
Worst case Read
Tot. Fragmented disk
128 KB / 8KB segments

Media
File System
( GPFS, AVID-ISIS, Isilon, Omneon Media Grid, XSAN, … )
Network
( Disk network, SAN )
Hard Disk
Storage Performance
3 Key Components:
100 %
Efficiency

9
FC-client Based
IP-client based
Clients
Clients
Clients
File
servers
Clients
Media IP Network
IBM-GPFS / SGI-CXFS /
HP-Lustre / ADIC-Stornext /
Nexsan / …
FC Network
File servers cluster
GPFS (IBM)
(General Parallel File System)
Parallel access
file system
Avid-Unity / Quantel /
SGI-CXFS /
Thomson GV / …
Video

Storage Capacity

SAN

Parallel Throughput

Proprietaire oplossingen
Schaalbaarheid???

Scalability
Reliability

MXF-AAF video/audio file
Media File System

File-based Media Production
X
SD Media
Storage
Storage
Throughput
Architecture needs to be “tuned” for media production
Classical IT
Storage
Storage
Capacity

Digital Media Factory Storage Clusters
Storage Cluster per Service Level

Go Live - 17 June 2007
Concurrent
engineering
Processing
during
ingest/transfer
Browse Clients
Craft editors
Draft
Processing
POST
Production
Media
Asset Mgmt
Subtitling
Analysis
INGEST
PLAY-OUT
IP network
Archiving
Annotation
8 GB P2 card
= 32 min video
DV25 (news)
Central
Storage
Follow-up
continuity
Post-
sonorisation
Editor-in-Chief
Central storage

Online searching, re-viewing and cutting

One-click re-purposing of content

Assertion

There is a mismatch between business requirements and state-of-the-art technology;
Media technology suppliers don’t sufficiently understandthe limitations of IT technology and conventional IT suppliers don’t have sufficient understanding of media production;
Proper research and development are essential...

2009 - Reconciliation of Requirements

Operational Excellence
Simplify system architecture
Standards implementation
Scale-out
Extend to non-news
Prepare for High-Definition
Production
Supply Chain Automation
Real-time co-production
Non-linear distribution
Integration of live and on demand
Accurate Item-level metadata

Objectives - Back-Office
1. Operational Excellence

Less applications reduce system integration
Metadata standards replace custom development

Master Data Management
Production and distribution
2. Scale out Infrastructure

Better applications reduce file transfers
State-of-the-art technology - Cost reduction

Editing
Mastering
Media Asset Mgnt
Ingest
Playout
Infrastructure –
Networks and Storage
3. Master Data Management

Rationale – Effective(!) re-use
Structured Metadata
Item-level metadata

Production Platform

Challenge – Operational Excellence
Editing
Mastering
Media Asset Mgnt
Ingest
Playout
Infrastructure –
Production Platform

System Integration Approach

Assumptions
Ad hoc plumbing (“data pump”) is a source of inconsistency;
Collaborative production and re-use of material rely on a single central repository.
Issues
None of the available state-of-the-art production applications have been designed to integrate and neither they have been originally designed for file-based production;
Commercially available MAM systems that lack essential functionality;
While an Enterprise Service Bus is assumed to protect overall consistency and performance, it is sensitive to complexity as well and may become a source of instability on its own.

Supply Chain Engine
MAMsystem
The level of Operational Excellencethat can be achieved by an Integrated System is determined by the extent to which individual applications have been designed to integrateand by the level of (metadata) standards implementation.

Lessons Learned – Principles of System Integration
Everything should be made as simple as possible, but not one bit simpler.

Challenge – Scale out Infrastructure
Editing
Mastering
Media Asset Mgnt
Ingest
Playout
Infrastructure –
Production Platform

High Definition Media Production Infrastructure
OT
Omneon
Omneon
Agility
IP network
IP network
OPAT
OPAT
OPAT
OPAT
OPAT
OPAT
OPAT
OPAT
OPAT
OPAT
OP1A
OP1A
OP1A
OP1A
OP1A
OP1A
OP1A
OP1A
Lres
OP1A
Lres
OP1A
OP1A
OPAT
OPAT
OP1A
OP1A
OPAT
OPAT
OPAT
OPAT
OPAT
OPAT
OPAT
OPAT
Lres
Output
Ardome
OT
ENC
ENC
ENC
ENC
ENC
ENC
ENC
ENC
ENC
ENC
ENC
ENC
ENC
ENC
ENC
ENC
ENC
ENC
ENC
ENC
MCRT
MCRT
MCRT
TSM
MCBE
MCBE
MCBE
TSM
BUBE
BUBE
BUBE
TSM
Polopoly
/import
//news
//feeds
/cut
Nieuws Playout
//lowres
//audio
MER
/wip
/sec
//sec
/archive
Data Tape
Archive
Data Tape
Backup
MCRT cluster
MCBE cluster
BUBE cluster
TSM2
TSM1
TSM2
TSM1
Workflow vs Dataflow:
A single Ingest operation causes 36 file transfers!
00
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
Browse Clients
GMII
Encoders
DV25
D10
MAM
Opslag
//news
//feeds
/import
Opslag
/wip
/archive
Opslag
//lowres
//audio
Opslag
/sec
Opslag
//sec
Precut
Ardex
22

Introduction: Issues – HD Digital Media Factory
OT
Omneon
Omneon
Agility
Output
OT
Polopoly
Nieuws Playout
MER
HD Media Infrastructure Issues

Complex Workflow -> Inefficient Dataflows
Increased Storage Capacity Requirements:HD ~= SD x 2 -> HD Storage Architecture???Backup/restore windows HD ~= SD x 2Reconsider# copies– storage protection
Cost:TargetHD ~= SD/4(not counting disk price erosion)
More media-formats:Transcoding becomesbottle-neck!

23
Geisha results IBC 2009

X
HD Media
Storage
HD Storage Architecture Requirements
Storage
Throughput
X
SD Media
Storage
“Tuned” Fibre Channel Architecture
Classical IT
Storage
Storage
Capacity
Geisha results IBC 2009

High Definition Media Infrastructure
State-of-the-Art

Currently 160TB storage capacity (3200 hrs HD) per cluster
Demonstrated troughput 40Gbps
Built-in Disaster Recovery
CAPEX - 2.2€ per GB

Objective 3 – Effective re-use
Media Asset Management Issues

Production Environment
No upfront selection causes information overload;
Multiple sources of more or less structured metadata;
Parallel sources cause dupplicates;
International context - multilingual

Infrastructure –
Production Platform

Objective 3 – Effective re-use
Media Asset Management Issues

Production Environment
No upfront selection causes information overload;
Multiple sources of more or less structured metadata;
Parallel sources cause dupplicates;
International context - multilingual

Professional Requirements
An item is relevant or it is not;
Retrieve all relevant items;
No false positives

Infrastructure –

Opportunities
Recognise workflow and trace dependancies;
Integrate with Product Engineering (scripts,...);
Computer Vision techniques may help.

Production Platform

The state of the Art…
archiefnummer : ALG 20010813 1
fragmentnummer : 1
reeks : 1000 ZONNEN EN GARNALEN
bandnummer : E03024404
formaat : DBCM
fragmenttitel : 1000 ZONNEN & GARNALEN
beeld : KL/PALPLUS
fragmentduur : 18 20
tekst : 0'00" TOERISTISCH REPORTAGEMAGAZINE OVERZICHT
ONDERWERPEN GENERIEK TOERISTISCH REPORTAGEMAGAZINE,
OVERZICHT ONDERWERPEN
0'50" VANDAAG : KUNSTENAAR LUC HOFKENS ONTWIERP EEN OASE
OP ZIJN DAKTERRAS IN BORGERHOUT DIE DOET DENKEN AAN DE
GRAND CANYON INTERVIEW MET LUC EN ZIJN VROUW
MARILOU BUITENBEELD DAK MET OMGEVING BUITENKANT
ARBEIDERSWONING, PANO OVER ROTSWANDEN, KRATEN MET WATER,
BEPANTING, FOTOALBUM MET VERLOOP WERKEN
4'00" JUNIOR : KLAARTJE ALAERTS, 13 JAAR WIL ASTRONAUTEN
WORDEN ZE BEZOEKT HETEUROSPACE CENTER METRUIMTEVEREN,
RAKETTEN SIMULATIE IN RUIMTEVEER, INTERVIEW, HEEFT EEN
UFO GEZIEN MAAKT ZELF KLEIN RAKETJE, SCHIET HET AF
7'50" DE SCHEURKALENDER : ARCHIEF RECLAMEFILM IBM
INTERVIEW MAURICE DE WILDE, EERSTE PERSOONLIJKECOMPUTER
trefwoorden : BELGIE; BORGERHOUT; ARTIEST; OASE; KUNST; GRAND
CANYON (NATUURGEBIED); DAK; TERRAS; INTERVIEW; EURO
SPACE CENTER; RUIMTEVAART; PC; BOOTTOCHT; RIJKDOM;
PASSAGIER; GASTRONOMIE; RESTAURANT; PERSONEEL;
VAKANTIE; BINNENBEELD; SCHIP; BECKERS LEEN; VRT;
LOTTO; RADIOOMROEPSTER; KLANKSTUDIO; UITVINDING;
BARBECUE; BETONMOLEN; IBM; RECLAMESPOT
rechthebbende : VRT
Opzoekscherm FILM Set: 16 Aantal: 1
blz 1 van 3
trefwoorden: ibm and vrt
archiefnummer: -
uitzendjaar: maand: dag:
fragmentnummer: fragmentduur:
reeks:
formaat: bandnummer:
aflevering: afleveringsnummer:
programma: uitzenddatum:
fragmenttitel:
tekst:
kategorie:
opnamedatum: opnamenummer:
journalist: rechthebbende:
SETS
The strings required for the operation are not defined
F11 F12 F13 F14 F17 F18 F19 F20 Ent
Eindigen Sets Refset Toon Vorige Volg/Leeg Thesaurus Commando Opzoeken

Shot Segmentation and Scene Recognition

Face recognition and identification

Media Asset Management - Opportunities

Professional context - trace dependencies
Scripts contain essential master data – integration with creative processes is a must
Computer Vision does not replace formal annotation, but substantially accelerates the process and increases the accuracy

!
An integrated data-model and a consistent application framework are the key to production automation and supply chain integration
(≠ Digitizing analogue and disintegrated workflows)

Conclusion
1. Operational Excellence

One set of numbers – reduce the number of apps
Less apps reduce the need for system integration
Replace custom development by proper standards

2. Scale out Infrastructure

Avoid file transfers
Cheaper systems for cost reduction

Editing
Mastering
Media Asset Mgnt
Ingest
Playout
3. Master Data Management

Trace dependancies
Integrate with creative processes
Explore and integrate automatic analysis tools

Infrastructure –
Production Platform

Broadband distribution
Data
Video
Audio
Communication
(Information)
Meta
Data
Meta
Data
Infrastructure –
Distribution via DVB,
IP or other
Production Platform

2004 – Live Streaming

Xmas 2007 – BBC iPlayer

Broadcast...
A customer can have a car painted any colour that he wants so long as it is black.(Henry Ford)

Good, better,...
Anywhere

“Live streaming”
Radioplayer software application
Quick win – “in series” live transcoding

Anytime

“Podcast”, “iPlayer”
On demand complements live offering
Major impact – metadata power-lifting

?
The Ultimate Radio Exp - myRadio

Mobile - Anywhere, anytime and impulse-driven
Seamless integration of live and on demand
Cross-platform continuity

The Ultimate Radio Exp(eriment)
myRadio @time of writing

Excellent quality where possible, lower bit-rate if necessary
Non-linear distribution assumes broadband distribution
Open distribution framework
Http adaptive streaming enables bandwidth-friendly distribution

http://myradio.vrt.com

Ongoing – Non-linear distribution
Seamless integration of Live and On demand

“Bookmark” by tagging
Pause, Back and Fast Forward
Radio search engine
Assemble myRadio

TO DO – Track each individual item

Audio segmentation
Speech recognition and indexing
Metadata harvesting (!!!)

Business Case for Radio
IP Distribution
+/- 5.000.000 hours per dag
à 128 kbps, 250 TB, 90PB per year
à 70.000€ per PB
Total – 6.300.000€
Vgl. Homepage (deredactie.be)

2MB
128 seconden high-def audio(!)

‘Supply Chain Integration’
Data
Video
Audio
Information
Communication
Information
Mgnt
Distribution to TV, PC and mobile via DVB and IP
Media Asset Mgnt
Infrastructure
(network and storage)

Trend – Production System Virtualisation

Trend - From « metadata » to CAD/CAM
?

Proof of Concept - Scoop
http://www.youtube.com
(search for “scoop”, “ibbt”, “CAD”)

Change...

47
http://medialab.vrt.be
http://myradio.vrt.be
Maarten.verwaest@vrt.be