Adaptive and Scalable Quality of Service Provisioning in Multirate Multicast Networks

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Multicasting has become increasingly important for real-time applications since it is the inherent mode ofdelivery in several of them, e.g. teleconferencing, audio and video broadcasting, etc. The Internet, however,does not provide end-to-end bandwidth or delay guarantees for unicast or for multicast data. As a result, anumber of multiple scale encoding schemes for real-time voice and video transmission have been developed;these schemes allow adaptation both to the available bandwidth and to the receiver capabilities by varyingthe number of levels of the information stream and therefore the corresponding bit rates. Thus, bandwidthand receiver adaptation of multi-level information streams, in multicast delivery in particular, is an issueof prime importance for the successful, large-scale deployment of those real-time applications. We proposeto investigate and develop methods for bandwidth sharing and adaptation in the context of multicast-based real-time applications. A set of fairness criteria based on which the performance of different schemescan be quantified and compared is introduced. A methodology for finding bandwidth allocations that areoptimal or suboptimal with respect to the different criteria is proposed. Scalability with the network size,amenability to distributed implementation in terms of required control information and speed of convergenceare adopted as prime criteria, in addition to optimality, in the evaluation of the different algorithms. Wepropose an approach for the design of the algorithms that allows the trade-off between optimality withrespect to the performance objective and practicality with respect to the other attributes (i.e. scalabilityetc.). A methodology for network control in multicasting in the case of unknown traffic and/or networkconditions is proposed as well. It involves explicit back-pressure based congestion notification feedback anddynamic per ow scheduling. Finally we propose a method for the design of congestion control policieswith the objective of maximizing an aggregate network utility. A relative comparison between the twoapproaches (fairness based and aggregate utility maximization) is also proposed in order to be able to selectthe most appropriate one in each case.