Methods for performance evaluation of VBR video traffic models
IEEE/ACM Transactions on Networking (TON)
Analysis, modeling and generation of self-similar VBR video traffic
SIGCOMM '94 Proceedings of the conference on Communications architectures, protocols and applications
Content-based browsing of video sequences
MULTIMEDIA '94 Proceedings of the second ACM international conference on Multimedia
A traffic for MPEG-coded VBR streams
Proceedings of the 1995 ACM SIGMETRICS joint international conference on Measurement and modeling of computer systems
Source models for VBR broadcast-video traffic
IEEE/ACM Transactions on Networking (TON)
Simple and efficient models for variable bit rate MPEG video traffic
Performance Evaluation - Special issue on applied probability modelling in telecommunication
The GBAR source model for VBR videoconferences
IEEE/ACM Transactions on Networking (TON)
RCBR: a simple and efficient service for multiple time-scale traffic
IEEE/ACM Transactions on Networking (TON)
Using adaptive linear prediction to support real-time VBR video under RCBR network service model
IEEE/ACM Transactions on Networking (TON)
Workload models of VBR video traffic and their use in resource allocation policies
IEEE/ACM Transactions on Networking (TON)
A gamma-based framework for modeling variable-rate MPEG video sources: the GOP GBAR model
IEEE/ACM Transactions on Networking (TON)
ARIMA time series modeling and forecasting for adaptive I/O prefetching
ICS '01 Proceedings of the 15th international conference on Supercomputing
Modelling user behaviour in networked games
MULTIMEDIA '01 Proceedings of the ninth ACM international conference on Multimedia
Statistical Digital Signal Processing and Modeling
Statistical Digital Signal Processing and Modeling
Motion-Based Video Representation for Scene Change Detection
International Journal of Computer Vision
Double exponential smoothing: an alternative to Kalman filter-based predictive tracking
EGVE '03 Proceedings of the workshop on Virtual environments 2003
The monitoring and early detection of internet worms
IEEE/ACM Transactions on Networking (TON)
Delving into internet streaming media delivery: a quality and resource utilization perspective
Proceedings of the 6th ACM SIGCOMM conference on Internet measurement
Standard Codecs: Image Compression to Advanced Video Coding
Standard Codecs: Image Compression to Advanced Video Coding
Can internet video-on-demand be profitable?
Proceedings of the 2007 conference on Applications, technologies, architectures, and protocols for computer communications
Prediction of MPEG-coded video source traffic using recurrent neural networks
IEEE Transactions on Signal Processing
Detection and representation of scenes in videos
IEEE Transactions on Multimedia
IEEE Transactions on Multimedia
Real-time VBR video traffic prediction for dynamic bandwidth allocation
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
IEEE Journal on Selected Areas in Communications
Predictive dynamic bandwidth allocation for efficient transport of real-time VBR video over ATM
IEEE Journal on Selected Areas in Communications
On the use of fractional Brownian motion in the theory of connectionless networks
IEEE Journal on Selected Areas in Communications
Statistical multiplexing of multiple time-scale Markov streams
IEEE Journal on Selected Areas in Communications
Real-time shot change detection over online MPEG-2 video
IEEE Transactions on Circuits and Systems for Video Technology
Video object segmentation using Bayes-based temporal tracking and trajectory-based region merging
IEEE Transactions on Circuits and Systems for Video Technology
Sparse basis selection: new results and application to adaptive prediction of video source traffic
IEEE Transactions on Neural Networks
Robust and efficient authentication of video stream broadcasting
ACM Transactions on Information and System Security (TISSEC)
Hi-index | 35.68 |
In this paper, we propose a model-based bandwidth prediction scheme for variable-bit-rate (VBR) video traffic with regular group of pictures (GOP) pattern. Multiplicative ARIMA process called GOP ARIMA (ARIMA for GOP) is used as a base stochastic model, which consists of two key ingredients: prediction and model validity check. For traffic prediction, we deploy a Kalman filter over GOP ARIMA model, and confidence interval analysis for validity determination. The GOP ARIMA model explicitly models inter and intra-GOP frame size correlations and the Kalman filter-based prediction maintains "state" across the prediction rounds. Synergy of the two successfully addresses a number of challenging issues, such as a unified framework for frame type dependent prediction, accurate prediction, and robustness against noise. With few exceptions, a single video session consists of several scenes whose bandwidth process may exhibit different stochastic nature, which hinders recursive adjustment of parameters in Kalman filter, because its stochastic model structure is fixed at its deployment. To effectively address this issue, the proposed prediction scheme harbors a statistical hypothesis test in the prediction framework. By formulating the confidence interval of a prediction in terms of Kalman filter components, it not only predicts the frame size but also determines validity of the stochastic model. Based upon the results of the model validity check, the proposed prediction scheme updates the structures of the underlying GOP ARIMA model. We perform a comprehensive performance study using publicly available MPEG-2 and MPEG-4 traces. We compare the prediction accuracy of four different prediction schemes. In all traces, the proposed model yields superior prediction accuracy than the other prediction schemes. We show that confidence interval analysis effectively detects the structural changes in the sample sequence and that properly updating the model results in more accurate prediction. However, model update requires a certain length of observation period, e.g., 60 frames (2 s). Due to this learning overhead, the advantage of model update becomes less significant when scene length is short. Through queueing simulation, we examine the effect of prediction accuracy over user perceivable QoS. The proposed bandwidth prediction scheme allocates less 50% of the queue(buffer) compared to the other bandwidth prediction schemes, but still yields better packet loss behavior.