It is important to smooth the quality variability and improve the utilization of the available network bandwidth in a streaming session from a scalable streaming server to the client over the network with bandwidth variation. In this paper, we propose an on-line smoothing scheduling algorithm for real-time scalable media stream with the variable network bandwidth and packet loss. This algorithm adopts a rate-distortion optimized framework and real-time scheduling scheme to select and schedule the packets according to the network status. It attempts to minimize the quality variability in client while at the same time maximizing the utilization of the variable network bandwidth. Experiments show that, compared with frame-based scheduling algorithm, our proposed on-line smoothing algorithm not only improves the quality in decoded video frames but also make the quality variation smoother.
In this paper, we propose a layer-based integrated real-time scheduling algorithm in a single scalable stream and an online
dynamic resource allocation algorithm among multiple concurrent users for scalable streaming media server over a network with packet loss and variable delay. The layer-based real-time scheduling algorithm efficiently schedules the packets in the buffer of the scalable streaming media server for transmission. The on-line resource allocation algorithm can allocate the server’s resource among all the concurrent streams fairly and improve the playback quality in client.
Simulation results show that our proposed algorithms outperform the frame-based scheduling algorithm and the off-line resource allocation algorithm in various situations with different round-trip times, channel errors, etc. The low complexity of the proposed algorithms also enables them to be applied in real-time applications.