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Multimedia Streaming via TCP: An Analytic Performance Study. Bing Wang, Jim Kurose, Prashant Shenoy, Don Towsley. Introduction. Under what circumstances can TCP streaming provide satisfactory performance? Live video streaming is constrained streaming
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Multimedia Streaming via TCP: An Analytic Performance Study Bing Wang, Jim Kurose, Prashant Shenoy, Don Towsley
Introduction • Under what circumstances can TCP streaming provide satisfactory performance? • Live video streaming is constrained streaming • Stored video streaming is unconstrained streaming
Outline • Analytic model • Simulation • Experiments • Effect of parameters on performance
Contribution of Paper • develop discrete-time Markov models for live and stored video streaming • explore how parameters (i.e. loss rate, round trip time, timeout value & playback rate) affect TCP streaming performance
Assumption • Average TCP throughput is no less than the video bitrate • Startup delay on the order of seconds • Videos are of constant bit rate (CBR)
Performance metrics • Fraction of late packets • no known metric directly for viewing quality
Model for TCP • time unit is round (length of a round = a round trip time) • Xi is the state of model in the ith round • Xi = (Wi, Ci, Li, Ei, Ri) • Wi = window size • Ci = delayed ACK behavior • Li = # packets lost in (i-1)th round • Ei = backoff exponent if in timeout state • Ri = 0 for new packet; =1 for retransmission
Model for constrained streaming • Yi is the state of the model in the ith round • Yi = (Xi, Ni) • Xi = state of TCP (mentioned before) • Ni = # early packets
Model for unconstrained streaming • As length go to infinity, # early packets go to infinity and fraction of late packets go to zero • use transient analysis • Yi is the state of the model in the ith round • Yi = Xi
Model for unconstrained streaming • use impulse reward to obtain transient distribution of Ni • impulse reward = difference % # packets received and played back in transition • Ni’= accumulation of the impulse reward up to ith round
Summary of results • fraction of late packets increases with length in live streaming, but decreases with length in stored streaming • performance increases with T/μ; beyond a certain point yields diminishing gain • performance is not solely determined by T/μ but also sensitive to parameters like R, p, T0 • For large R, p and T0, either long startup delay or T/μ greater than 2 is needed for low fraction of late packets
Implication • large fraction of streaming video clips are encoded at 300Kbps • most DSL and cable modem connection support 750Kbps – 1.5Mbps • TCP streaming is adequate for broadband users
Conclusion • Discrete-time Markov models for live and stored video streaming • Simulation and experiments show models are accurate • Study effect of various parameters on performance with the models