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Oscillation	
  Compensating
Dynamic	
  Adaptive	
  Streaming	
  over	
  HTTP
Christopher	
  Mueller,	
  Stefan	
  Lederer,	
  Reinhard Grandl,	
  and	
  Christian	
  Timmerer
Alpen-­‐Adria-­‐Universität Klagenfurt	
  (AAU)	
  w Faculty	
  of	
  Technical	
  Sciences	
  (TEWI) w Department	
  of	
  Information	
  
Technology	
  (ITEC)	
  w Multimedia	
  Communication	
   (MMC) w Sensory	
  Experience	
  Lab	
  (SELab)
http://blog.timmerer.com w http://selab.itec.aau.at/w http://dash.itec.aau.at w christian.timmerer@itec.aau.at
Chief	
  Innovation	
  Officer	
  (CIO)	
  at	
  bitmovin	
  GmbH
http://www.bitmovin.com w christian.timmerer@bitmovin.com
Slides:	
  http://www.slideshare.net/christian.timmerer
IEEE	
  ICME	
  2015,	
  June	
  29	
  – July	
  3,	
  2015
July	
  2,	
  2015 IEEE	
  ICME	
  2015 2
Submission	
   deadline:	
  November	
  27,	
  2015
http://www.mmsys.org/ |	
  http://mmsys2016.itec.aau.at/ |	
  @mmsys2015
Outline
• Introduction,	
  Motivation,	
  Problem	
  Statement
• Metrics	
  and	
  Tools
• Buffer-­‐based	
  Adaptation	
  Algorithm	
  with	
  
Oscillation	
  Detection	
  and	
  Compensation
• Experimental	
  Results
• Conclusions	
  and	
  Future	
  Work
July	
  2,	
  2015 IEEE	
  ICME	
  2015 3
Over-­‐The-­‐Top	
  – Adaptive	
  Media	
  Streaming
• In	
  a	
  Nutshell	
  …
Adaptation logic is within the
client, not normatively specified
by the standard,subject to
research and development
July	
  2,	
  2015 IEEE	
  ICME	
  2015 4
Why	
  do	
  we	
  do	
  that?
• HTTP-­‐based	
  multimedia	
  streaming	
  
is	
  being	
  massively	
  deployed
– Accounts	
  for	
  more	
  than	
  60%	
  of	
  
Internet	
  traffic in	
  peak	
  periods
• Client-­‐centric	
  approach
– Adaptation	
  algorithm/logic
– Client	
  behavior	
  subject	
  to	
  research
– Throughput-­‐basedvs.	
  buffer-­‐based
• What	
  happens	
  when	
  multiple	
  
clients	
  compete with	
  each	
  other?
July	
  2,	
  2015 IEEE	
  ICME	
  2015 5
Source:	
  Global	
   Internet	
   Phenomena	
   Report:	
  2H	
  2014	
  
What’s	
  the	
  problem?
• Big	
  Buck	
  Bunny	
  with	
  different	
  
representations
• Throughput-­‐based	
  adaptation
• Common	
  test	
  setup w/	
  two	
  
clients	
  and	
  varying	
  bandwidth
July	
  2,	
  2015 IEEE	
  ICME	
  2015 6
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Without	
  cache
What’s	
  the	
  problem?
• Big	
  Buck	
  Bunny	
  with	
  different	
  
representations
• Throughput-­‐based	
  adaptation
• Common	
  test	
  setup w/	
  two	
  
clients	
  and	
  varying	
  bandwidth
July	
  2,	
  2015 IEEE	
  ICME	
  2015 7
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With	
  cache
Our	
  metrics	
  and	
  tools!
• Adaptation-­‐specific
– Quality	
  switching	
  variance:	
  change	
  of	
  representation
– Oscillation	
  variance:	
  includes	
  direction	
  of	
  switching
• Buffer-­‐specific
– Buffer	
  model	
  restricting	
  available	
  quality	
  levels
• Based	
  on	
  buffer	
  fill	
  state
• Fitting	
  to	
  available	
  quality	
  levels	
  &	
  network	
  conditions
• Different	
  behavior:	
  linear,	
  exponential,	
  logarithmic
– Worst	
  case	
  buffer:	
  minimum	
  buffer	
  fill	
  state	
  in	
  seconds	
  that	
  shall	
  
be	
  available	
  prior	
  to	
  the	
  download	
  of	
  segment
July	
  2,	
  2015 IEEE	
  ICME	
  2015 8
Our	
  approach!	
  (1/2)
• Buffer-­‐based	
  adaptation	
  algorithm	
  
including:
– Oscillation	
  detection
– Oscillation	
  compensation
– Fully	
  client-­‐centric
• Oscillation	
  factor
– Depends	
  on	
  quality	
  switching	
  
variance and	
  oscillation	
  variance
– Increases	
  when	
  both	
  metrics	
  
become	
  different
July	
  2,	
  2015 IEEE	
  ICME	
  2015 9
Our	
  approach!	
  (2/2)
• Buffer-­‐based	
  adaptation
– c	
  …	
  min.	
  buffer	
  level	
  (aka	
  steady	
  state)
– b	
  …	
  fitting	
  based	
  on	
  a	
  given	
  c
– a	
  …	
  max.	
  representation	
  bitrate
• Compensation	
  algorithm
– Low	
  &	
  high comp.
July	
  2,	
  2015 IEEE	
  ICME	
  2015 10
/RJDULWKPLFg%LWUDWHg5HVWULFWLRQ
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Our	
  results!	
  (1/2)
July	
  2,	
  2015 IEEE	
  ICME	
  2015 11
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Our	
  results!	
  (2/2)
July	
  2,	
  2015 IEEE	
  ICME	
  2015 12
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With	
  cache
Our	
  conclusions!
• We	
  highlighted	
  some	
  issues
– Throughput-­‐based	
   adaptation	
  logics
– Clients	
  competing for	
  bandwidth
• In	
  this	
  paper
– Buffer-­‐based	
  adaptation	
  models
– Clients	
  metrics for	
  oscillation	
  detection
– Oscillation	
  compensation algorithm
– Increase	
  streaming	
  performance	
  – higher	
  throughput	
   &	
  less	
  quality	
  
switches
• Important:	
  client-­‐centric	
  approach
– Enables	
  scalability,	
  maintains	
  advantages of	
  DASH,	
  and	
  is	
  deployed!
• Future	
  work
– Large-­‐scale	
  evaluations
July	
  2,	
  2015 IEEE	
  ICME	
  2015 13
http://www.dash-­‐player.com/
Thank	
  you	
  for	
  your	
  attention
...	
  questions,	
  comments,	
  etc.	
  are	
  welcome	
  …
Priv.-­‐Doz.	
  Dipl.-­‐Ing.	
  Dr.	
  Christian	
  Timmerer
Associate	
  Professor
Alpen-­‐Adria-­‐Universität Klagenfurt,	
  Department	
  of	
  Information	
  Technology	
  (ITEC)
Universitätsstrasse 65-­‐67,	
  A-­‐9020	
  Klagenfurt,	
  AUSTRIA
christian.timmerer@itec.uni-­‐klu.ac.at
http://research.timmerer.com/
Tel:	
  +43/463/2700	
  3621	
  Fax:	
  +43/463/2700	
  3699
©	
  Copyright:	
  Christian	
  Timmerer
14July	
  2,	
  2015 IEEE	
  ICME	
  2015
July	
  2,	
  2015 IEEE	
  ICME	
  2015 15
Submission	
   deadline:	
  November	
  27,	
  2015
http://www.mmsys.org/ |	
  http://mmsys2016.itec.aau.at/ |	
  @mmsys2015

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Oscillation Compensating Dynamic Adaptive Streaming over HTTP

  • 1. Oscillation  Compensating Dynamic  Adaptive  Streaming  over  HTTP Christopher  Mueller,  Stefan  Lederer,  Reinhard Grandl,  and  Christian  Timmerer Alpen-­‐Adria-­‐Universität Klagenfurt  (AAU)  w Faculty  of  Technical  Sciences  (TEWI) w Department  of  Information   Technology  (ITEC)  w Multimedia  Communication   (MMC) w Sensory  Experience  Lab  (SELab) http://blog.timmerer.com w http://selab.itec.aau.at/w http://dash.itec.aau.at w christian.timmerer@itec.aau.at Chief  Innovation  Officer  (CIO)  at  bitmovin  GmbH http://www.bitmovin.com w christian.timmerer@bitmovin.com Slides:  http://www.slideshare.net/christian.timmerer IEEE  ICME  2015,  June  29  – July  3,  2015
  • 2. July  2,  2015 IEEE  ICME  2015 2 Submission   deadline:  November  27,  2015 http://www.mmsys.org/ |  http://mmsys2016.itec.aau.at/ |  @mmsys2015
  • 3. Outline • Introduction,  Motivation,  Problem  Statement • Metrics  and  Tools • Buffer-­‐based  Adaptation  Algorithm  with   Oscillation  Detection  and  Compensation • Experimental  Results • Conclusions  and  Future  Work July  2,  2015 IEEE  ICME  2015 3
  • 4. Over-­‐The-­‐Top  – Adaptive  Media  Streaming • In  a  Nutshell  … Adaptation logic is within the client, not normatively specified by the standard,subject to research and development July  2,  2015 IEEE  ICME  2015 4
  • 5. Why  do  we  do  that? • HTTP-­‐based  multimedia  streaming   is  being  massively  deployed – Accounts  for  more  than  60%  of   Internet  traffic in  peak  periods • Client-­‐centric  approach – Adaptation  algorithm/logic – Client  behavior  subject  to  research – Throughput-­‐basedvs.  buffer-­‐based • What  happens  when  multiple   clients  compete with  each  other? July  2,  2015 IEEE  ICME  2015 5 Source:  Global   Internet   Phenomena   Report:  2H  2014  
  • 6. What’s  the  problem? • Big  Buck  Bunny  with  different   representations • Throughput-­‐based  adaptation • Common  test  setup w/  two   clients  and  varying  bandwidth July  2,  2015 IEEE  ICME  2015 6 5HTXHVWHGq0HGLDq%LWUDWH 0ESV 3 4 f S c 5HTXHVWHGq0HGLDq%LWUDWH %XIIHU 6HFRQGV 3 43 f3 S3 c3 6HFRQGV 3 o3 433 4o3 f33 fo3 S33 %XIIHU 6HFRQGV 3 o3 433 4o3 f33 fo3 S33 Without  cache
  • 7. What’s  the  problem? • Big  Buck  Bunny  with  different   representations • Throughput-­‐based  adaptation • Common  test  setup w/  two   clients  and  varying  bandwidth July  2,  2015 IEEE  ICME  2015 7 5HTXHVWHGq0HGLDq%LWUDWH 0ESV 3 4 f S c 5HTXHVWHGq0HGLDq%LWUDWH %XIIHU 6HFRQGV 3 43 f3 S3 c3 6HFRQGV 3 o3 433 4o3 f33 fo3 S33 %XIIHU 6HFRQGV 3 o3 433 4o3 f33 fo3 S33 With  cache
  • 8. Our  metrics  and  tools! • Adaptation-­‐specific – Quality  switching  variance:  change  of  representation – Oscillation  variance:  includes  direction  of  switching • Buffer-­‐specific – Buffer  model  restricting  available  quality  levels • Based  on  buffer  fill  state • Fitting  to  available  quality  levels  &  network  conditions • Different  behavior:  linear,  exponential,  logarithmic – Worst  case  buffer:  minimum  buffer  fill  state  in  seconds  that  shall   be  available  prior  to  the  download  of  segment July  2,  2015 IEEE  ICME  2015 8
  • 9. Our  approach!  (1/2) • Buffer-­‐based  adaptation  algorithm   including: – Oscillation  detection – Oscillation  compensation – Fully  client-­‐centric • Oscillation  factor – Depends  on  quality  switching   variance and  oscillation  variance – Increases  when  both  metrics   become  different July  2,  2015 IEEE  ICME  2015 9
  • 10. Our  approach!  (2/2) • Buffer-­‐based  adaptation – c  …  min.  buffer  level  (aka  steady  state) – b  …  fitting  based  on  a  given  c – a  …  max.  representation  bitrate • Compensation  algorithm – Low  &  high comp. July  2,  2015 IEEE  ICME  2015 10 /RJDULWKPLFg%LWUDWHg5HVWULFWLRQ 0D[LPXPgSYDLODEOHg%LWUDWH 0LQLPXPgSYDLODEOHg%LWUDWH SOORZHGg0HGLDg%LWUDWHg>0ESV@ u A v l b %XIIHUg)LOOg6WDWXVg>h@ u usv usb usd usp A
  • 11. Our  results!  (1/2) July  2,  2015 IEEE  ICME  2015 11 5HTXHVWHGq0HGLDq%LWUDWH 0ESV 3 4 f S c 5HTXHVWHGq0HGLDq%LWUDWH %XIIHU 6HFRQGV 3 43 f3 S3 c3 %XIIHU 2VFLOODWLRQq)DFWRU 3 3pf 3pc 3pn 3pl 4 6HFRQGV 3 o3 433 4o3 f33 fo3 S33 2VFLOODWLRQq)DFWRU 6HFRQGV 3 o3 433 4o3 f33 fo3 S33 5HTXHVWHGq0HGLDq%LWUDWH 0ESV 3 4 f S c 5HTXHVWHGq0HGLDq%LWUDWH %XIIHU 6HFRQGV 3 43 f3 S3 c3 %XIIHU 2VFLOODWLRQq)DFWRU 3 3pf 3pc 3pn 3pl 4 6HFRQGV 3 o3 433 4o3 f33 fo3 S33 2VFLOODWLRQq)DFWRU 6HFRQGV 3 o3 433 4o3 f33 fo3 S33 W i t h o u t c a c h e W i t h c a c h e
  • 12. Our  results!  (2/2) July  2,  2015 IEEE  ICME  2015 12 /RJDULWKPLFg×XIIHUg0RGHOg3GDSWDWLRQ 7KURXJKSXWg0HDVXUHPHQWg3GDSWDWLRQ 4XDOLWg6ZLWFKLQJg9DULDQFHg>0ESVð@ pAy TîpAy 7LPHg>6HFRQGV@ A QA pAA pQA nAA nQA TAA Without  cache /RJDULWKPLFg×XIIHUg0RGHOg3GDSWDWLRQ 7KURXJKSXWg0HDVXUHPHQWg3GDSWDWLRQ 4XDOLWg6ZLWFKLQJg9DULDQFHg>0ESVð@ pAy TîpAy 7LPHg>6HFRQGV@ A QA pAA pQA nAA nQA TAA With  cache
  • 13. Our  conclusions! • We  highlighted  some  issues – Throughput-­‐based   adaptation  logics – Clients  competing for  bandwidth • In  this  paper – Buffer-­‐based  adaptation  models – Clients  metrics for  oscillation  detection – Oscillation  compensation algorithm – Increase  streaming  performance  – higher  throughput   &  less  quality   switches • Important:  client-­‐centric  approach – Enables  scalability,  maintains  advantages of  DASH,  and  is  deployed! • Future  work – Large-­‐scale  evaluations July  2,  2015 IEEE  ICME  2015 13 http://www.dash-­‐player.com/
  • 14. Thank  you  for  your  attention ...  questions,  comments,  etc.  are  welcome  … Priv.-­‐Doz.  Dipl.-­‐Ing.  Dr.  Christian  Timmerer Associate  Professor Alpen-­‐Adria-­‐Universität Klagenfurt,  Department  of  Information  Technology  (ITEC) Universitätsstrasse 65-­‐67,  A-­‐9020  Klagenfurt,  AUSTRIA christian.timmerer@itec.uni-­‐klu.ac.at http://research.timmerer.com/ Tel:  +43/463/2700  3621  Fax:  +43/463/2700  3699 ©  Copyright:  Christian  Timmerer 14July  2,  2015 IEEE  ICME  2015
  • 15. July  2,  2015 IEEE  ICME  2015 15 Submission   deadline:  November  27,  2015 http://www.mmsys.org/ |  http://mmsys2016.itec.aau.at/ |  @mmsys2015