Smoothing and Congestion Control Algorithms for Stored Continuous Media

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Future high-speed computer networks are projected to carry a dizzying array of networked multimedia applications including digital libraries, video and image servers, distance learning and collaboration, networked virtual environments, and entertainment. A common thread among these applications is the so-called "continuous" nature of their data. In continuous media (CM) data, strict timing relationships exist, which define the schedule by which CM data must be rendered (e.g., a video displayed or audio played out). In a network setting, the playout timing constraints, the rate variability of specific CM such as variable bit rate (VBR) video, the possibility of packet loss and delay within the network, and the desire to use network resources efficiently together combine to make the transport of CM data an exceptionally challenging problem.An important class of continuous media is stored continuous media. This differs from live continuous media in several ways. First, CM traffic characteristics are typically known ahead of time. Second, CM data is often characterized by a more relaxed requirement as to when playout can begin. Last, unlike live CM data, stored CM data does not provide the opportunity for changing the encoding rate in response to network congestion. In this proposal principal investigators (PIs) outline research aimed at the design and evaluation of algorithms and network transport protocols for supporting stored continuous media applications. These algorithms and protocols accommodate and exploit the unique features of stored CM (e.g., known traffic characteristics and the ability to transmit data further in advance of its playout time, the time-sensitive nature of CM playout).The proposed research divides broadly into two areas:1) Smoothing of stored continuous media. The PIs propose to develop and evaluate work-ahead smoothing algorithms for transmitting stored video to a client subject to client and network buffering constraints. The goal is to develop algorithms that compute CM transmission schedules that require a minimal use of network resources (e.g., have the smallest peak rate requirement, the smallest bandwidth requirement variability, and the smallest buffering requirements). 2) Congestion control for stored continuous media. The PIs propose to develop and evaluate rate control algorithms that adaptively vary the transmission rate of a stored CM source in response to congestion within the network. Of particular interest are the resulting performance tradeoffs among interfering CM and non-CM connections.The proposed research has a particular emphasis on performance -- evaluating and understanding performance in a wide variety of settings, as well as formally establishing properties (e.g., optimality) of specific approaches. Other important themes in the proposed work include the importance of supporting client interactivity (e.g., developing approaches with small startup delays, examining the tradeoff between startup delay and resource requirements), the development of stored CM algorithms and protocols for a variety network settings (e.g., different network service models, as well as in unicast and multicast scenarios), and the complementary mix of theory and experimentation embodied in the proposed research.