VBR video delivery under constrained resources using motion-aware optimal frame selection
This paper proposes an optimal frame selection scheme for motion-aware VBR video delivery under both channel and buffer size constraints. Our objective is to find a feasible set of frames that can maximize the video's accumulated motion metrics without violating any constraint. We use a discrete-time model to monitor client buffer occupancy status at each frame and find the optimal frame selection path with a Viterbi based algorithm. By eliminating non-optimal frame states and considering inter-frame dependencies, our proposed scheme achieves a low computational cost of O(TN), where T is a parameter related to the client buffer size B and N is the total number of frames. The experimental results show that T can be several magnitudes smaller than B. In addition, we investigate the impact of startup latency and propose a way to find the optimal preload