High quality video streaming using content-awareadaptive frame scheduling with explicit deadlineadjustment

We propose an application layer algorithm for content-aware adaptive video frame scheduling on bandwidth varying channels. The proposed approach includes an iterative algorithm which sequentially uses the rate constraint and delay constraint for video frames to arrive at a decision to drop/ send video frames. In addition to our base algorithm, we also propose an explicit deadline adjustment (EDA) algorithm. The main idea behind EDA relates to the sender adjusting/ postponing the deadline of an important frame which is estimated to miss its deadline by actively dropping one (or more) less important next frame(s) and sending the deadline adjusted/ postponed frame to be displayed in place of the next dropped frame(s). The rate-distortion (R-D) performance of our proposed approach and its comparison with prior art method is shown.

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