A lossless smoothing algorithm for compressed video
IEEE/ACM Transactions on Networking (TON)
Receiver-driven layered multicast
Conference proceedings on Applications, technologies, architectures, and protocols for computer communications
SAVE: an algorithm for smoothed adaptive video over explicit rate networks
IEEE/ACM Transactions on Networking (TON)
Smoothing variable-bit-rate video in an Internetwork
IEEE/ACM Transactions on Networking (TON)
Quality adaptation for congestion controlled video playback over the Internet
Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication
Addressing Heterogeneity and Scalability in Layered Multicast CongestionControl
Addressing Heterogeneity and Scalability in Layered Multicast CongestionControl
Rate adaptive multimedia streams: optimization and admission control
IEEE/ACM Transactions on Networking (TON)
Flow-level QoS for a dynamic load of rate adaptive sessions sharing a bottleneck link
Computer Networks: The International Journal of Computer and Telecommunications Networking
IEEE Transactions on Mobile Computing
Online smoothing of variable-bit-rate streaming video
IEEE Transactions on Multimedia
Smoothing, statistical multiplexing, and call admission control for stored video
IEEE Journal on Selected Areas in Communications
A prefetching protocol for continuous media streaming in wireless environments
IEEE Journal on Selected Areas in Communications
High-performance prefetching protocols for VBR prerecorded video
IEEE Network: The Magazine of Global Internetworking
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This paper addresses a practical problem in our everyday use of streaming media on the Internet: as a user observes the buffering of a media stream with an uncertain transfer rate, when should that user initiate playback of the stream? The tension is that initiating playback prematurely will increase the likelihood of buffer starvation, while a delay in initiating playback is undesirable because it necessitates waiting. Three policies are studied: the optimal policy (exploiting full knowledge of the transfer process), the optimal static policy (the expected value of the optimal policy), and an online policy assuming only knowledge of the transfer rate observed thus far. Lower and upper bounds are derived on the optimal policy as well as the associated minimum cost; these bounds are expressed in terms of a (random) hitting time of the transfer process. Simulation results for a Markov modulated transfer rate process identify static and online policies as near-optimal depending on the time scale of the transfer rate process and the duration of the stream.