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Distributed Video Streaming  Over Internet Thinh PQ Nguyen and Avideh Zakhor Berkeley, CA, USA Presented By Sam
Agenda ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Motivation ,[object Object]
Motivation ,[object Object],[object Object],[object Object]
Assumptions ,[object Object],2Mbps 0.8Mbps 0.4Mbps
Assumptions ,[object Object]
Assumptions ,[object Object],[object Object]
Contributions Overview ,[object Object],[object Object],[object Object]
Scenario ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Protocol Receiver algorithm Sender algorithm
Bandwidth Estimation ,[object Object],B : The current available TCP-friendly bandwidth between each sender and the receiver (Upper bound for the TCP-friendly sending rate) Trto : TCP timeout R : estimated round-trip time in seconds (using moving average of RRT over a fixed interval) P : estimated loss rate (number of lost packets / total number of packets sedting over a fixed interval) S : TCP segment size in bytes
Rate Allocation Algorithm ,[object Object],During the interval (t, t +  ∆) F(t) total number of loss packet L(I, t) estimated loss rates S(I, t) estimated sending rates Sreq(t) is the required bit rate for the encoded video B(I, t) TCP-friendly estimated bandwidth
Rate Allocation Algorithm ,[object Object],[object Object]
Systolic window ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Packet Partition Algorithm ,[object Object],[object Object],[object Object],[object Object],[object Object]
Packet Partition Algorithm ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Packet Partition Algorithm ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Packet Partition Algorithm ,[object Object],[object Object],[object Object]
Packet Partition Algorithm ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Choice of Synchronization Sequence Number ,[object Object],[object Object],[object Object]
Simulation 20 γ 500bytes Packet size 100ms Ф 50ms Delay for sender 2 0.1*S(i) w 40ms Delay for sender 1
Simulations T = 0 to 2s. Starts sending control packets T = 25s, senders send using the algorithms T = 200s, 25 of 100 TCP sources from 1 stop sending T = 400s, 10 new TCP sources start and stop at random
Comparison
Comments ,[object Object],[object Object],[object Object],[object Object]
Conclusion ,[object Object],[object Object],[object Object]

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Distributed Video Streaming over Internet

  • 1. Distributed Video Streaming Over Internet Thinh PQ Nguyen and Avideh Zakhor Berkeley, CA, USA Presented By Sam
  • 2.
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  • 20. Simulation 20 γ 500bytes Packet size 100ms Ф 50ms Delay for sender 2 0.1*S(i) w 40ms Delay for sender 1
  • 21. Simulations T = 0 to 2s. Starts sending control packets T = 25s, senders send using the algorithms T = 200s, 25 of 100 TCP sources from 1 stop sending T = 400s, 10 new TCP sources start and stop at random
  • 23.
  • 24.

Notes de l'éditeur

  1. Having multiple senders is also a diversification scheme in that it combats unpredictability of congestion in the Internet.
  2. If the route between a particular sender and the receiver experiences congestion during streaming, the receiver can redistribute streaming rates among other senders, thus resulting in smooth video delivery.
  3. That’s nothing to do with the multi-server video streaming
  4. If there is congestion on a shared link between two senders, then changing the sending rate of one sender may affect the traffic conditions of the other one.
  5. it is preferable to download the entire video in a non-real time fashion before playing it back. The focus is on the the limiting factor in streaming is packet loss and delay due to congestion along the streaming path, rather than the physical bandwidth limitations of the last hop.
  6. the receiver coordinates transmissions from multiple senders based on the information received from the senders.
  7. F(t) total number of loss packet
  8. each sender i also satisfies the constraints in order to share bandwidth fairly with other TCP traffic. The algorithm minimizes F(t) , the number of lost packets during the interval ) , ( . + t t , given instantaneous feedback, and assuming that the estimated loss rate and TCP-friendly available bandwidth are accurate. The proof for this is included in the Appendix.
  9. This is because it takes D(j) for the control packet to arrive ar the sender j N for the kth packet to be sent by sender j D for it arrive at the reeiver sigma
  10. All the senders receive the same control packet from the receive Only use the information in the control packet to update the Ak All use the same equation to do so…r
  11. To illustrate the algorithm, we show a simple example in which, there are two senders, each sending packets at equal rate. As shown in Figure 6, the Sync sequence number is 10. The top line with vertical bars denotes the playback time for the packets. The middle and the bottom lines indicate the time to send packets for senders 1 and 2, respectively. In this scenario, packet 10 will be sent by sender 1 since the estimated difference between playback and its receive time for packet 10 is greater than that of sender 2. Next, packet 11 will be sent by sender 2 for the same reason.
  12. If n is as large as 0.1 then probability is 10-6
  13. Cross/ circle.. Set11… So set 6
  14. the loss rate of scenario two can be 2.5 times larger than that of scenario two. And always over 1 Next, we compare the mean squared error (MSE) of pixel values between the sent frame and the received frame. Since there quite a large number of frames, we further average the MSE for every video frame over a period of 5s. Higher MSE represents lower fidelity of the video due to lost packets. As shown in Figure 14, most of the time the MSE for scenario one lower than that of scenario two.
  15. Finally, there has been work on detecting the shared congestion points of different routes [9] based on the correlation of packet loss and delay between routes. These correlations can be used ahead of time to improve the performance of our approach.