EE689 Lecture 14

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EE689 Lecture 14

• Review of Last lecture
• Receiver-driven Layered Multicast

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Receiver-driven Multicast

• Sender based schemes dont scale well as number
  of receivers increase
• Receiver based schemes scale better
• Receivers can decide the level of reliability
  needed - level of quality desired etc.
• Receivers can coordinate and reduce the work for
  loss recovery

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Layered Multicast

• Receivers and network connectivity heterogeneous
• Difficult to deal with packet losses
• Receivers with higher connectivity should be
  allowed to get a better quality picture
• Receivers with lower connectivity can get better
  quality through layered video than random losses
  of packets in flat video

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RLM

• RLM - developed at LBL
• Café Mocha - at TAMU
• Use layered video coding
• Allow receivers to subscribe to different layers
• Organize multicast into several groups - each
  group corresponds to a different layer

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Network Congestion

• Network congestion - dynamic
• With higher traffic, multicast should backoff to
  lower layers
• With less traffic, could get higher quality
• Have to allow receivers to drop/add layers
  dynamically
• Add/Join Experiments

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Add-Join Experiments

• Receivers add a layer to see if there is enough
  BW
• If packet losses go up, then experiment
  unsuccessful - dont add layer
• Associate a timer with each layer
• On a failure, double the timer for next join
  experiment

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Join Experiments

• On unsuccessful joins, all the receivers on the
  same subnet could learn from failure
• Increase everyones timer on a failed expt.
• If everyone tries an experiment at the same time,
  
• results can be different than individual attempts
• can cause increased traffic

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Join Experiments

• Add a random component to join experiments
• If a join experiment is in progress, dont
  initiate another one
• multicast a join experiment
• allows shared learning, increase your timer on
  someone elses failed experiment
• convergence time can be high
• priorities in network affect RLM scalability

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Simultaneous joins

• Simultaneous join experiments may happen on
  different layers
• If experiment fails
• join experiment at the highest layer gt failed
• join experiment a a lower layer gt not sure,
  could be due to other experiment
• Start a Measurement mode to determine if
  long-term congestion persists.

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States of RLM

• Steady state (S), Drop state (D), Measurement
  state (M) and Hysteresis (H)
• Hysteresis state allows not reacting to transient
  congestion caused by join experiments
• use a detection timer T

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Issues

• Latency Scalability
• Session Scalability
• Bandwidth Heterogeneity
• Superposition

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Network Implications

• Receiver Consensus
• One bad user can cause trouble for subnet
• Group Maintenance
• add/join should happen quickly (IGMP)
• Fairness
• multiple multicasts -how to share BW
• how to ensure multicast doesnt hog BW

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TCP-friendly Multicast

• Arrange layers in an exponentially increasing
  data rates
• In steady state, packet drop gt congestion, drop
  a layer
• If layers are doubling in data rates, dropped
  layer reducing multicast rate by half gt TCP
  friendly

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Summary

• Receiver-driven layered multicast works
• Critically dependent on timers
• Much work is being done to make many of these
  mechanisms more efficient
• Need for reducing overhead
• add/join experiments