Opportunistic transport for stored video delivery over wireless networks: Optimal anticipative and causal approximations

This paper considers the design of application-layer opportunistic transport mechanisms for stored video over a slowly time-varying wireless channel. We focus on two simple key ideas. The first is that video should be transmitted when the channel capacity is high, e.g., exceeds a threshold; by doing so one can exploit temporal diversity in channel variations to reduce the system utilization as well as energy expenditures. Second, such opportunistic transmissions should be coupled with the status of the user's playback buffer to ensure uninterrupted video playback. We explore how to optimize such systems in several scenarios. We start with the single-user anticipative case (i.e. future channel variations are known) and show that a piecewise constant thresholding scheme is optimal, i.e., minimizes the system utilization without playback buffer starvation. This case not only provides a baseline for the best one can do, but may be applicable in cases where users' mobility is known or predictable, allowing the future channel capacity to be anticipated, e.g., based on history or a navigation system. We then study the multiuser case, where one can exploit not only the future temporal but also multiuser diversity. Finally, we consider the multiuser causal scenario(where the future channel is unknown, but statistics might be inferred) and develop a receiver-oriented adaptive opportunistic video transport mechanism using a stochastic approximation approach. Our simulations show that the proposed schemes can achieve an up to 70% reduction in the system utilization.