The efficient transmission of variable-bit-rate (VBR) video streams is complicated by the burstiness that video compression standards such as MPEG introduce. Most of the existing techniques concentrate on stored video traffic smoothing or real-time video traffic smoothing. However, there is a growing number of live video applications, such as video-casts of courses or television news, where many clients may be willing to tolerate a playback delay of several seconds or minutes in exchange for a smaller throughput requirement. Bandwidth smoothing for these live video applications is referred to as online smoothing. In this paper, in order to measure the effectiveness of online video smoothing methods, we propose a benchmark algorithm, which provides an upper bound on some of the performance metrics in the smoothing results. Based on this algorithm, we found that significant discrepancy exists between the results produced by the existing online smoothing methods and the upper bound. With this observation, we focus on designing algorithms that can improve the smoothing results. Experimental results show that the proposed algorithms make considerable improvements compared to existing smoothing methods.
All Science Journal Classification (ASJC) codes
- Computer Networks and Communications