On balancing between transcoding overhead and spatial consumption in content adaptation
Proceedings of the 8th annual international conference on Mobile computing and networking
Post-processing of MPEG2 coded video for transmission at lower bit rates
ICASSP '96 Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 04
Transcoding GIF images to JPEG-LS
IEEE Transactions on Consumer Electronics
New architecture for dynamic frame-skipping transcoder
IEEE Transactions on Image Processing
Architectures for MPEG compressed bitstream scaling
IEEE Transactions on Circuits and Systems for Video Technology
A frequency-domain video transcoder for dynamic bit-rate reduction of MPEG-2 bit streams
IEEE Transactions on Circuits and Systems for Video Technology
Overview of fine granularity scalability in MPEG-4 video standard
IEEE Transactions on Circuits and Systems for Video Technology
Drift compensation for reduced spatial resolution transcoding
IEEE Transactions on Circuits and Systems for Video Technology
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Transcoding is a core technique that is used in providing quality-of-service (QoS) adaptive multimedia streaming service. Many studies have examined how best to perform transcoding and reduce computation overhead. However, the issue of when to transcode has not been adequately studied in previous research. This paper addresses this issue 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.