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Is Dynamic Multi-Rate Worth the Effort?

Is Dynamic Multi-Rate Worth the Effort?. Matthew Peace 04.14.04 Wireless Information Networking Group. Problem. With the progression toward continuous media distribution, end systems are expected to be cooperative in determining/adapting transmission rates

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Is Dynamic Multi-Rate Worth the Effort?

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  1. Is Dynamic Multi-Rate Worth the Effort? Matthew Peace 04.14.04 Wireless Information Networking Group

  2. Problem • With the progression toward continuous media distribution, end systems are expected to be cooperative in determining/adapting transmission rates • In a multi-rate multicast, several desirable fairness properties can be achieved

  3. Problem • A static multi-rate system may only be able to support coarse grained adaptation • Using a dynamic multi-rate system might be more reasonable

  4. Purpose of Paper • To find the possible benefit of a dynamic multi-rate multicast solution with respect to inter-receiver fairness • Does this gain compensate for higher implementation costs associated with a coding scheme and dynamic partitioning?

  5. Inter-Receiver Fairness • “satisfaction” of a receiver given by ui utility function, which is a function of gj (its actual rate) and theoretical fair allocation ri • Optimality occurs when gj = ri

  6. Receiver Utility Function

  7. Inter-Receiver Fairness • Goal in this system is to maximize collective satisfaction of receivers of a multicast session (sum of the utility values) • Uj=Utility for set of receivers Gjis maximized when the worst receiver’s gj = ri

  8. Inter-Receiver Fairness Where lj is the the data rate of the jth layer L = number of layers (groups) in a session N = number of receivers in a session Ri = the ith receiver ri = the theoretical fair allocation for Ri Gj = the set of receivers subscribed to layers 1 to j nj= the number of receivers in Gj gj = the cumulative data rate in Gj

  9. Inter-Receiver Fairness US = the session Utility (sum over layers)

  10. Protocol Issues • Optimal Rate Estimation • Receivers determine when to send feedback • Optimal rate derived from an equation modeling long term TCP throughput • Measure the Lost Rate Event • Measure the Round Trip Time

  11. Protocol Issues (Cont.) • Feedback Suppression • Receiver is allowed to send feedback only if it’s utility degradation (uopt – ui) exceeds a certain threshold Δ ui = uopt X (1 – αj) • αj derivation • Size of Gj must be taken into consideration • The larger the size of Gj the higher the utility degradation must be in order to send feedback • αj is a function of the number of receivers in G

  12. Protocol Issues (Cont.) • Avoiding Leave Action • If a receiver calculates the theoretical rate to be less than the current receiving rate, it may leave the highest layer immediately • To avoid coarse-grained quality degradation: • Over a time interval T, the sender is collecting receiver feedback for each layer • Each receiver calculates ri. If ri < gj a report is sent to the sender and the receiver waits for the next announcement of the sending rates • Only if new rate has not been lowered to accommodate a receiver’s reported rate, then the receiver is forced to leave a group

  13. Experiments • Generation of 500 rates, with min and max rates set • The inter-receiver fairness is maximized when all receivers are served optimally or

  14. Experiments (Cont.) • “Goodness” of a session determined by ratio of USto USopt

  15. Results • Single-Rate vs. Multi-rate • Optimality occurs when number of layers L approaches number of receivers N, but higher number of layers causes more overhead • First experiment studies the effect of increases the number of layers for a logarithmic utility function and a linear utility function

  16. Results (Cont.) Normal Distribution of receiver rates mean = 1248kbps and varying standard deviation = 2k

  17. Results (Cont.) Uniform Distribution with varying range [rmin, 2k X rmin]

  18. Results (Cont.) • Static Layers vs. Dynamic Layers • Rminand Rmaxused to calculate predefined static layer rates and compared with situation where adaptive techniques are used on the actual distribution of the rates

  19. Results (Cont.)

  20. Results (Cont.) • Assumed a trimodal distribution to find the rates for the static layers. • Then, the effect of receivers drifting from last mode to an additional one was simulated

  21. Results (Cont.)

  22. Conclusions • Adaptation in a multi-rate multicast mode may increase the overall satisfaction with only a few layers in an unpredictable environment, thus offsetting the cost of added complexity to the system

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