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IEEE JSAC Special Issue Adaptive Media Streaming. Submissions by April 1 Details at http://www.jsac.ucsd.edu/Calls/adaptivemediastreamingCFP.pdf. Packet Video Workshop 2013 San Jose, CA (@ Cisco). December 12/13, 2013 (Right after PCS 2013) Submissions by m id June

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ieee jsac special issue adaptive media streaming

IEEE JSAC Special IssueAdaptive Media Streaming

Submissions by April 1

Details at

http://www.jsac.ucsd.edu/Calls/adaptivemediastreamingCFP.pdf

packet video workshop 2013 san jose ca @ cisco

Packet Video Workshop 2013San Jose, CA (@ Cisco)

December 12/13, 2013 (Right after PCS 2013)

Submissions by mid June

http://pv2013.itec.aau.at/

server based traffic shaping for stabilizing oscillating adaptive streaming players

Server-Based Traffic Shaping for Stabilizing OscillatingAdaptive Streaming Players

Saamer Akhshabi, Lakshmi Anantakrishnan, Constantine Dovrolis

Ali C. Begen

briefly
Briefly …
  • Problem
    • When multiple adaptive streaming players compete for bandwidth, we have several problems:
      • Instability
      • Unfairness
      • Bandwidth underutilization
  • Objective
    • A server-based traffic shaping solution to mitigate the oscillation problem without significant loss in utilization
outline
Outline
  • Overview of adaptive streaming over HTTP
  • Multiple-player competition
  • Stabilization method and demonstration
  • Results
  • Conclusions
outline1
Outline
  • Overview of adaptive streaming over HTTP
  • Multiple-player competition
  • Stabilization method and demonstration
  • Results
  • Conclusions
adaptive streaming over http
Adaptive Streamingover HTTP
  • Media is split into “chunks”
  • Each chunk corresponds to a certain amount of content
  • Each chunk is encoded atmultiple bitrates
  • Clients request chunks based on their estimate of available bandwidth

From IIS Smooth Streaming Website

typical behavior of a player
Typical Behavior of a Player
  • One chunk per HTTP request
  • Two states:
    • Buffering
      • Request chunks as fast as possible
      • Build up the playback buffer
    • Steady
      • Request a new chunk every T seconds
      • Keep buffer size constant
  • ON-OFF download pattern
  • Estimate avail-bwwith running average of per-chunk TCP throughput measurements
outline2
Outline
  • Overview of adaptive streaming over HTTP
  • Multiple-player competition
    • Instability
    • Bandwidth underutilization
    • Unfairness
  • Stabilization method and demonstration
  • Results
  • Conclusions
simple model two competing players
Simple Model: Two Competing Players
  • Shared link
  • Capacity C
  • Fair share = C/2
  • Based on the temporal overlap of the ON-OFF periods of the players three performance problems can arise
    • Instability
    • Unfairness
    • Bandwidth underutilization
  • Two competing adaptive streaming players
  • Steady-State
  • Full buffers
  • Ideal TCP
    • A single active connection gets entire capacity C
    • Two active connections share the capacity fairly receiving C/2 each
the root c ause of oscillations
The Root Cause of Oscillations

ON

ON

ON

ON

  • Both players measure per-chunk throughput of more than C/2
  • Overestimate the fair share (f=C/2)
  • They will request bitrate greater than f, if available
    • Oscillations
    • Bandwidth underutilization
    • Unfairness

One player ON

Chunk download

ON

ON

ON

Both players OFF

Both players ON

Tseconds

outline3
Outline
  • Overview of adaptive streaming over HTTP
  • Multiple-player competition
  • Stabilization method and demonstration
    • Server-based shaping solution
    • Experimental setup
    • Stabilization method
  • Results
  • Conclusions
outline4
Outline
  • Overview of adaptive streaming over HTTP
  • Multiple-player competition
  • Stabilization method and demonstration
    • Server-based shaping solution
    • Experimental setup
    • Stabilization method
  • Results
  • Conclusions
traffic shaping s olution basic idea
Traffic Shaping Solution: Basic Idea
  • A server-side stabilizer module
    • Client independent
    • Basically, a reactiveand adaptive traffic shaper
  • The stabilizer
    • Remains inactive if there is no client-side instability
    • When instability is detected, stabilizer shapes requested video chunks at the rate of a lower profile
      • Client will then measure lower throughput, and it will return (and hopefully stabilize) to a lower profile
outline5
Outline
  • Overview of adaptive streaming over HTTP
  • Multiple-player competition
  • Stabilization method and demonstration
    • Server-based shaping solution
    • Experimental setup
    • Stabilization method
  • Results
  • Conclusions
experimental methodology
Experimental Methodology
  • DummyNet
  • Stabilizer
  • DummyNet
    • Sets the capacity of the share bottleneck
  • Wireshark
    • Captures the traffic for offline analysis
  • Server
    • Hosts the video content in multiple bitrates
    • Host for stabilizer
  • Clients
    • Simpler player
      • Logs internal parameters
      • Does not render video
    • Smooth Streaming player
implementation
Implementation
  • Server: Smooth Apache module:
    • http://smoothstreaming.code-shop.com/trac/wiki/Mod-Smooth-Streaming-Apache
  • Shaping done with Apache mod_bw module:
    • http://bwmod.sourceforge.net
  • Shaping module is modified to implement the stabilizer
outline6
Outline
  • Overview of adaptive streaming over HTTP
  • Multiple-player competition
  • Stabilization method and demonstration
    • Server-based shaping solution
    • Experimental setup
    • Stabilization method
  • Results
  • Conclusions
relation between shaping rate and chunk encoding rate
Relation between Shaping Rate and Chunk Encoding Rate

Ideal Case

Shaping

Player-1

  • Eliminate OFF periods by shaping each chunk so that its download takes about T seconds
  • Shape the chunk to the average encoding rate for that chunk
  • In practice, the shaping rate is set to a slightly higher value than the encoding rate (r/c)
    • Shaping slack parameter c (0.7 in this study)

ON

ON

ON

ON

ON

Player-2

ON

ON

Tseconds

Tseconds

ON

ON

ON

ON

Both players OFF

Both players ON

Chunk download

One player ON

relation between shaping rate and chunk encoding rate1
Relation between Shaping Rate and Chunk Encoding Rate

Real Scenario

Shaping

Player-1

  • Eliminate OFF periods by shaping each chunk so that its download takes about T seconds
  • Shape the chunk to the average encoding rate for that chunk
  • In practice, the shaping rate is set to a slightly higher value than the encoding rate (r/c)
    • Shaping slack parameter c (0.7 in this study)

ON

ON

ON

ON

ON

Player-2

ON

ON

Tseconds

Tseconds

ON

ON

ON

ON

Both players OFF

Both players ON

Chunk download

One player ON

oscillation detection
Oscillation Detection
  • Detecting direction changes
    • Direction change defined as a change in the requested profile (upshift or downshift) that is different than the last such change
  • When two or more direction changes occur within W successive chunks, an oscillation is detected and the player is flagged as unstable
    • Parameter W is the detection window size
initial shaping r ate s election
Initial Shaping Rate Selection
  • Goal is to find the highest sustainable profile
  • Consider a set of candidate profiles
    • Highest profile is obviously not sustainable
    • Shaper starts by setting the initial shaping rate to the next highest profile
experiment with the simpler player
Experiment with the Simpler Player
  • Six video profiles between 0.7 and 5 Mbps
  • Bottleneck capacity 10 Mbps
  • Four players are competing

Player-1 starts streaming

Three more player join

Two players leave

shaping rate d ecrease
Shaping Rate Decrease
  • During shaping the server distinguishes between oscillations
    • Due to OFF periods
      • Shaping rate should be decreased
    • Due to short-term avail-bw reductions
      • No reason to modify the shaping rate
  • How to distinguish between the two cases?
    • Based on the requested profiles in the last W chunks

Short-term available bandwidth drops detected

shaping rate i ncrease
Shaping Rate Increase
  • The server occasionally estimates the available bandwidth
    • De-activates shaping for randomly chosen chunks
    • Measure the connection’s throughput by looking at the ratio cwnd/rtt
  • Increase the shaping rate if the estimated available bandwidth is higher than the shaping rate

Two players leave

Avail-bw increases

Shaping rate increases

Abort procedure activated

outline9
Outline
  • Overview of adaptive streaming over HTTP
  • Multiple-player competition
  • Stabilization method and demonstration
  • Results
    • Performance metrics
    • Number of competing players
    • In the presence of a TCP bulk transfer
    • Mix of players
  • Conclusions
outline10
Outline
  • Overview of adaptive streaming over HTTP
  • Multiple-player competition
  • Stabilization method and demonstration
  • Results
    • Performance metrics
    • Number of competing players
    • In the presence of a TCP bulk transfer
    • Mix of players
  • Conclusions
performance metrics
Performance Metrics
  • Instability
    • Fraction of successive chunks in which the requested bitrate is not constant
    • For each client:
      • Increase: 1, Decrease: -1, Constant: 0
    • The number of 1’s and -1’s divided by the total number of chunk requests
  • Utilization
    • Aggregate throughput of all players divided by avail-bw
outline11
Outline
  • Overview of adaptive streaming over HTTP
  • Multiple-player competition
  • Stabilization method and demonstration
  • Results
    • Performance metrics
    • Number of competing players
    • In the presence of a TCP bulk transfer
    • Mix of players
  • Conclusions
number of competing p layers instability
Number of Competing PlayersInstability
  • Unshaped players
    • Instability metric peaks at some mid-range N value
  • Shaped players
    • Instability metric significantly lower
    • We cannot reject the hypothesis that the mean instability is constant as N is increased
number of competing p layers utilization
Number of Competing PlayersUtilization
  • Between shaped and unshaped players
    • For some values of N, the utilization metric does not show a statistically significant difference
    • For other values of N, the difference in the actual utilization is not large
outline12
Outline
  • Overview of adaptive streaming over HTTP
  • Multiple-player competition
  • Stabilization method and demonstration
  • Results
    • Performance metrics
    • Number of competing players
    • In the presence of a TCP bulk transfer
    • Mix of players
  • Conclusions
in the presence of a tcp bulk transfer
In the Presence of a TCP Bulk Transfer
  • Instability metric is much less in the shaped case
  • Aggregate utilization is high in both cases
    • The TCP flow tends to fill up the bottleneck
  • TCP connection takes up the largest share of the bottleneck’s capacity
  • BW=10 Mbps
  • 3 players
  • (shaped
  • or
  • unshaped)
  • Greedy
outline13
Outline
  • Overview of adaptive streaming over HTTP
  • Multiple-player competition
  • Stabilization method and demonstration
  • Results
    • Performance metrics
    • Number of competing players
    • In the presence of a TCP bulk transfer
    • Mix of players
  • Conclusions
mix of players
Mix of Players
  • Shaped players
    • have the lowest instability
    • Their presence helps to also stabilize the competing unshaped players
  • Utilization is slightly less in the mixed-player experiments
  • BW=12 Mbps
  • Two
  • shaped
  • and
  • two
  • unshaped
  • players
outline14
Outline
  • Overview of adaptive streaming over HTTP
  • Multiple-player competition
  • Stabilization method and demonstration
  • Results
  • Conclusions
conclusions
Conclusions
  • Competition between adaptive streaming players can lead to performance problems
    • Instability, unfairnessand bandwidth underutilization
  • Root cause is the ON-OFF behavior of players during Steady-State
    • Players overestimate the fair share if their ON periods are not perfectly synchronized (which is rarely the case)
  • Traffic shaping can help mitigate instability
    • (Upon oscillations) by shaping chunks at a lower bitrate pushing players to switch to the lower profile
    • Without incurring significant loss in bandwidth utilization