Client-driven price selection for scalable video streaming with advertisements
MMM'12 Proceedings of the 18th international conference on Advances in Multimedia Modeling
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This paper considers scalable delivery of streaming video content with advertisements. It proposes a highly accurate waiting-time prediction algorithm that estimates the expected number of viewed ads by utilizing detailed information about the system state and the applied scheduling policy. It also proposes a pricing scheme based on the expected waiting times, which include the ads’ viewing times. The revenues generated by the ads are used to subsidize the price and are allocated to clients proportionally to their expected waiting times. The envisioned system presents the client with an updated menu of the supported videos (such as full-length featured movies) along with the corresponding ads’ viewing times and prices. We analyze the effectiveness of the proposed prediction algorithm and pricing scheme in terms of many metrics, considering numerous design and workload parameters, and capturing purchasing capacity and willingness models.