Hybrid transcoding for QoS adaptive video-on-demand services

Abstract

Transcoding is a core technique that is used in providing quality-of-service (QoS) adaptive video-on-demand service. Many studies have examined how best is to perform transcoding and reduce computation overhead. However, the question of when to transcode has not been adequately studied in previous research. This paper addresses this question and presents a simple and intelligent approach that can be used to reduce both disk bandwidth and space requirements. Our approach determines the optimum time to apply transcoding by considering the potential benefits that can be realized. For instance, in order to save disk bandwidth for frequently accessed content, it pre-creates and stores multiple QoS versions. On the other hand, in order to save disk space for rarely accessed content, it stores only a single QoS version and performs transcoding on the fly. The key is to find the optimal threshold between pre-created multiple QoS versions and on-demand transcoding. We compute the optimal threshold by using a mathematical model. A simulation-based experiment to evaluate the effectiveness of our new approach highlights three advantages. First, our method effectively reduces both disk bandwidth and space requirements. Second, our technique is more efficient for skewed access patterns. Third, the threshold computed by our mathematical model results in improved performance regardless of environmental parameters.