Abstract
We propose an analytical model based on renewal reward theory to investigate the dynamics of an on-demand streaming service. At the same time, we also propose a simple method combining a method of multicasts and method of unicasts that can reduce the download rate from the streaming server without causing delay. By modeling the requests as a Poisson arrival and using renewal reward theory, we study the dynamics of this streaming service and derive the optimal combination of unicast and multicast methods. We even show how to estimate the fluctuation of download rates of a streaming service.
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Toyoizumi, H. (2009). Analytical Model of On-Demand Streaming Services Based on Renewal Reward Theory. In: Yue, W., Takahashi, Y., Takagi, H. (eds) Advances in Queueing Theory and Network Applications. Springer, New York, NY. https://doi.org/10.1007/978-0-387-09703-9_2
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DOI: https://doi.org/10.1007/978-0-387-09703-9_2
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