Video Transmission Over Varying Bandwidth Links

1
Video Transmission Over Varying Bandwidth Links

• MTP Final Stage Presentation
• By Laxmikant Patil
• Under Guidance of
• Prof. Sridhar Iyer

2
Presentation Outline

• Introduction Motivation
• Problem Definition
• Related Work
• Traffic Pattern based Adaptive Multimedia
  Multicast (TPAMM) Architecture
• Solution Strategy
• Simulation Results
• Conclusion
• References

3
Introduction Motivation

• Key Terms
• Playout Rate The rate at which video is shown at
  client
• Delay Tolerant Applications Clients can tolerate
  some delay before playout starts
• e.g. DEP offering live courses to remote
  students, Live concert streaming, MNCs training
  employees across cities
• Startup Latency Maximum duration of time client
  is ready to wait before playout starts

4
Introduction Motivation (Contd)

• Need for Adaptive Mechanisms
• Heterogeneity of receivers capabilities
• Transmission capabilities
• Displaying capabilities
• Heterogeneity of receivers requirements
• Delay tolerance values
• Minimum acceptable quality

5
Introduction Motivation (Contd)

• 3 ways to transfer data from source to client
• Streaming solution
• Partial download
• Complete download

C
6
Problem Definition

• Objective is to use to overcome the problem of
  variations in link bandwidth and provide
  consistent video quality to the client.
• We propose to use startup latency and prediction
  model based approach to overcome this

7
Example

• Given
• Startup latency 5 min
• Length of video L 60 min
• aavg ?

8
Related work

• SAMM Multilayering Video is encoded as base
  layer and enhancement layers.
• Client receive number of layers depending on
  their capabilities
• Objective is to decide number of layers
  encoding rates of each layer
• KRTCR Transcoding Changes the encoding rate
  of the video file to desired rate
• Transcoding only at source
• Transcoding at relay nodes
• AIMA Buffer-based adaptation uses occupancy of
  buffer on transmission path as a measure of
  congestion
• AVMI Simulcast Source maintains different
  quality stream and receiver switches across
  streams. Combination of single-rate multicast and
  multiple-unicast.

9
TPAMM Architecture (Traffic Pattern based
Adaptive Multimedia Multicast)
10
Solution strategy

• Single hop topology
• Multi hop topology
• Multicast tree topology
• Prediction window offset computation

11
Single hop topology

• Find

12
Single hop topology (Contd)

• Need to find Critical points during transmission

13
Single hop topology (Contd)

• Critical points at t 100 sec
• (Accumulated Bw) lt (Consumed Bw)

No Critical points (Accumulated Bw) gt
(Consumed Bw)
14
Multi hop topology (Source-Relay-Client Scenario)
15
Multihop scenario
S
R1
R2
Rn
C
16
Multicast Tree Topology
17
Prediction Window Time-Offset Computation
Prediction window
Last Prediction window

• Startup latency
• Duration of video Encoding rate
• All predictions values per interval

• We modify algorithm to work for prediction window
  size, by computing time-offset.
• Startup latency for next window Current Startup
  latency time-offset
• Duration of video for next window Current
  duration of video - time-offset

18
Prediction Window Time-Offset Computation
(Contd)
Prediction window
Last Prediction window

• Following values are known
• Encoding rate for current feedback interval
  (e.g. 60 kbps)
• Transmission rate for current feedback interval
  (e.g. 90 kbps)
• Feedback interval duration (e.g. 10 sec)
• Actual_playout_duration_Tx (A) is computed as
• (Encoding rate / Transmission rate ) Feedback
  interval duration 15 sec
• Expected_playout_duration_Tx (E) is computed as
• (current_playout_time)
  Feedback interval duration 10 sec
• (current_playout_time current_startup_latency)
• Time-offset (Actual_playout_duration_Tx)
  (Expected_playout_duration_Tx)
• Time-offset for this example is 5 sec.

19
Simulation Results

• Effect of Delay Tolerance on Encoding Rate

• As Delay Tolerance increases Encoding Rate also
  increases

20
Simulation Results (Contd)

• Effect of Prediction Window size on Video Quality

• Parameter Standard deviation of encoding rate
• As prediction window size increases, variations
  in video quality are reduced.
• With small increase in prediction window size,
  there is significant drop in variation.

21
Simulation Results (Contd)

• Effect of Prediction Window size on Video Quality

• As prediction window size increases, variations
  in video quality are reduced.

22
Simulation Results (Contd)

• Maximize Minimum Video Quality During Playout

• Minimum Video Quality throughout playout is
  maximized in TPAMM scheme.

23
Conclusion

• We have introduced a class of algorithms known as
  Traffic Pattern based Adaptive Multimedia
  Multicast (TPAMM) algorithms.
• In TPAMM scheme abrupt link bandwidth variations
  are not reflected at client side, ensuring good
  user perceived video quality.
• TPAMM scheme maximizes the minimum video quality
  during playout.

24
References

1. SAMM Brett Vickers, Albuquerque and Tatsuya
   Suda, Source-adaptive multi-layered multicast
   algorithm for real-time video distribution.
   IEEE/ACM Transactions on Networking,
   8(6)720-733, 2000.
2. AVMI Jiangchuan Liu, Bo Li and Ya-Qin Zhang.
   Adaptive video multicast over the internet. IEEE
   Multimedia, 10(1)22-33,2003.
3. KRTCR Rajeev Kumar, JS Rao, AK Turuk, S.
   Chattopadhyay and GK Rao A protocol to support
   Qos for multimedia traffic over internet with
   transcoding www.ee.iastate.edu/gmani/tiw-2002/int
   ernet-qos.pdf
4. AIMA X. Wang and H. Schulzrinne. Comparison of
   adaptive internet multimedia applications. In
   IEICE Trans. COMMUN. 1999.