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Is Dynamic Multi-Rate Worth the Effort?

This paper explores the benefits of dynamic multi-rate multicast solutions for inter-receiver fairness, comparing implementation costs. It delves into receiver utility functions, optimal satisfaction, and protocol issues like rate estimation, feedback suppression, and avoiding leave actions. Experiment results on optimal satisfaction, rate distributions, and static vs. dynamic layers are presented to derive insightful conclusions.

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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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