An Adaptive Congestion Control Mechanism for Video Multicast
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An Adaptive Congestion Control Mechanism for Video Multicast






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An Adaptive Congestion Control Mechanism for Video Multicast An Adaptive Congestion Control Mechanism for Video Multicast Presentation Transcript

  • An Adaptive Congestion Control Mechanism for Video Multicast Yi Pan Yuji Imai
  • Necessity of Congestion Control of Video Multicast
    • Users are now getting more and more interested in video data transmission.
    • Video data consumes a lot of network resource and users want to find a way to transmit satisfactory video stream without severely interfering current data streams.
    • Adaptive congestion control of video multicast will help to achieve this goal.
  • Current Research Related to Video Multicast Congestion Control
    • TCP-friendly congestion control ([SF00],[SF97],[SCH98])
      • current usage is only under unicast connections
      • proved fairness with traditional TCP traffic
      • existing protocol can be used to implement the congestion control (RTP/RTCP)
    • Multi-layer encoded multimedia ([SAMM], [BTW])
      • adaptive to heterogeneity of bandwidth in video multicast.
      • the promising solution to encode video for multi-receivers
    • Multi-layer multicast congestion control ([INFO98], [RLM])
      • under classical multicast model
      • need the assistance of intermediate nodes
  • Fundamental Problems in Multilayer Video Multicast
    • Multicast branch pruning problem:
      • Behind a bottleneck, leaving of the only receiver subscribing to a layer should immediately alleviate the congestion at the bottleneck while in Internet Standard Multicast (ISM), it will take long time.
    • Receiver interfering problem:
      • Behind a bottleneck, a receiver who adds to a new layer may cause congestion at the bottleneck. That may cause other receivers react by lowering their subscribing level which is not desirable feature of the video multicast.
    • Finding of potential bandwidth:
      • Behind a single bottleneck, when there are receivers subscribing to different layers of video stream, a receiver adding to a new layer may not need extra bandwidth at the bottleneck, which means there is potential bandwidth exists at the bottleneck.
    • Multicast group managing problem:
      • the problem is with the number of the multicast group needed for multi-layer video multicast.
        • Fixed number of multicast group may have some “empty” groups which waste network resource.
        • Adaptive number of multicast group will take long time to establish/delete a new multicast group under ISM architecture.
  • Goals of Video Multicast Congestion Control
    • Quick convergence of video congestion control
    • Adaptiveness of video congestion control to receivers in various situations.
    • Fairness of congestion control of video transmission competing with other traditional methods (TCP-like)
    • Those issues are stated in [SF00],[INFO98],[SCH98].
  • Our Proposal of Adaptive Congestion Control over XCAST
    • Combination of good techniques:
      • there exists unicast congestion control which fixes the “too sensitive” feature of TCP.
      • multi-layer encoded video stream satisfies heterogeneous receiver connections
      • XCAST solves the problem of joining/leaving overhead in intermediate routers
      • Sender-driven multicast congestion control has benefits of fine-tuned, quick convergence,etc.
  • Our Solution
    • Sender-driven congestion control for multi-layer encoded video stream.
      • Receiver make estimation of its available bandwidth and send the feedback to sender.
      • Sender adjusts the number of layers and the rate of each layer based on the feedback messages.
      • Make the receivers in the same layer as an XCAST group.
        • With XCAST, it’s now possible to use multiple dynamic flows to transmit multiple layers in sender-driven scheme.
    • Integrate Traffic Control to congestion control for video transmission.
      • Equation-based Congestion Control
        • Receiver reports estimated Round Trip Time and estimated loss rate p.
        • Sender calculates transmit rates based on a certain equation, group receivers in different layers, and send out video stream
      • FEC congestion control
        • using FEC encoding to let receivers recover the loss
    • Employ XCAST to solve fundamental problems with multicast video transmission.
      • XCAST groups are explicit and branch pruning can be done within a round trip time (as long as the “quit” message arrives the sender)
      • We can employ intelligent aggregation algorithms to make optimal grouping of receivers in dynamic number of layers
      • XCAST does not need the assistance of intermediate nodes
  • Simulation and Expected Results
    • Simulation Scenario:
      • compare our scheme with the existing multicast congestion control in:
        • convergence time for congestion control
        • fairness between different users
        • adaptive to different connections
        • overhead of congestion control
        • average goodput for receivers
        • fairness when competing with other flows using TCP-like congestion control
    • Expected results are:
      • quick convergence time for congestion control
      • adaptive to heterogeneous connections under limited number of receivers
      • low overhead incurred in network
      • higher average goodput for receivers
      • good fairness competing with traditional TCP-like congestion control mechanisms
  • Technical Details
    • Equation Based Congestion Control:
      • basically the equation based congestion control is based on the following equation:
      • So we propose the receiver send feedback to sender including the RTT and loss rate p it estimates so that the sender can calculate the estimated acceptable rate.
    • Dynamic receiver grouping:
      • Transmission rate to each receiver is calculated by sender and the sender need to optimally partition receivers to groups with a specific transmission rate for each group.
      • Algorithm to find the optimal partition of receivers should achieve the goals of reducing the number of groups and maximize total goodput.
    • Receiver interference problem:
      • two approaches:
        • Adjusted equation based control: adjust the equation let higher layer receiver to be more sensitive to loss and RTT.
        • Employ “deaf” period for lower layer receivers: after a new higher layer receiver being added, allow lower layer receivers to be “deaf” to loss and RTT for a while.
      • Approach 1:
        • receivers make estimation of RTT and loss rate p based on different transmission rate:
        • Advantage: no need for sender to be aware of where the bottleneck is.
        • Disadvantage: the lower layer receivers still suffer for a short time, though less influenced.
      • Approach 2
        • Notify affected receivers to be “deaf” for a period of time to let the newly added high layer receiver quiet down.
        • Advantage: Lower layer receivers will not be affected at all.
        • Disadvantages:
          • Sender needs to be aware of where the bottleneck is and who are behind the bottleneck.
          • Necessary adjustment of rate may be delayed by the “deaf” period.
      • One additional notation of receiver interference:
        • Since we transmit different layer in different XCAST group, that means we can use different flows to transmit different layers.
        • With the help of current DiffServ Architecture, we can easily isolate those flows so that different layers will have much less impact on each others.
    • Potential bandwidth finding:
      • May need to build tractable list of receivers in each layer. (need to discuss)
        • probing packets for each destination are sent out periodically.
        • The branching records are kept in the probing packets and are sent back to sender.
        • Sender uses those branching records to build up the sink tree.
        • Only need max(RTT) of all the receivers to build that sink tree.
      • As long as we get such information, it is easy to find potential bandwidth in bottleneck. So it’s safe to add this new receiver for high layer.
      • This technique is kind of congestion avoidance technique, not congestion control.
  • Future Research
    • Prove the effectiveness of the architecture in future Internet providing DiffServ services for QoS requirements
    • Future extension:
      • explore impact of combining XCAST and resource allocation in this architecture.
      • explore impact of QoS routing and its impact on this architecture.
  • Reference List
    • [SF00] S. Floyd, M. Handley, J. Padhye, J. Widmer, “Equation-Based Congestion Control for Unicast Applications”, SIGCOMM 2000
    • [SF97] J. Mahdavi, S. Floyd, “TCP-Friendly Unicast Rate-Based Flow Control”, Jan 1997
    • [SCH98] D. Sisalem, H. Schulzrinne, “The Loss-Delay Based Adjustment Algorithm: A TCP-Friendly Adaptation Scheme”, Proc. of NOSSDAV'98, July, Cambridge, UK
    • [SAMM] B. Vickers, C. Albuquerque, T.Suda, “Source Adaptive Multi-Layered Multicast Algorithms for Real-time Video Distribution”, IEEE ToN, 1999
    • [INFO98] L. Vicisano, J. Crowcroft, “TCP-like Congestion Control for Layered Multicast Data Transfer” Proc. of IEEE INFOCOM'98.
    • [BTW] J.C. Bolot, T. Turletti, I.Wakeman, “Scalable Feedback Control for Multicast Video Distribution in the Internet”, Proc. of ACM SIGCOMM, pp58-67, Aug. 1994.
    • [RLM] S. McCanne, V. Jacobson, M. Vetterli, “Receiver-Driven Layered Multicast”, Proc. of ACM SIGCOMM, pp117-130, Aug. 1996.