Adaptive linear prediction of MPEG video traffic

Xu, Wenjun; Qureshi, Asfandyar

doi:10.1109/isspa.1999.818114

Cited by 24 publications

(15 citation statements)

References 14 publications

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“…The average line-rate of video traffic is 2 Mb/s and it is MPEG coded. According to Akaike Information Criteria (AIC) [11] , the best step number of the linear predictor is less than 12, therefore we set the step number p = 12 for the predictor in our simulation. The computing complexity is O (12).…”

Section: Simulation Resultsmentioning

confidence: 99%

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Dynamic wavelength and bandwidth allocation using adaptive linear prediction in WDM/TDM ethernet passive optical networks

Guo

2009

J. Shanghai Jiaotong Univ. (Sci.)

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Hybrid wavelength-division-multiplexing (WDM)/time-division-multiplexing (TDM) ethernet passive optical networks (EPONs) can achieve low per-subscriber cost and scalability to increase the number of subscribers. This paper discusses dynamic wavelength and bandwidth allocation (DWBA) algorithm in hybrid WDM/TDM EPONs. Based on the correlation structure of the variable bit rate (VBR) video traffic, we propose a quality-ofservice (QoS) supported DWBA using adaptive linear traffic prediction. Wavelength and timeslot are allocated dynamically by optical line terminal (OLT) to all optical network units (ONUs) based on the bandwidth requests and the guaranteed service level agreements (SLA) of all ONUs. Mean square error of the predicted average arriving rate of compound video traffic during waiting period is minimized through Wiener-Hopf equation. Simulation results show that the DWBA-adaptive-linear-prediction (DWBA-ALP) algorithm can significantly improve the QoS performances in terms of low delay and high bandwidth utilization.

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Section: Simulation Resultsmentioning

confidence: 99%

“…Adaptive linear prediction [10,11] is one of the most effective methods. According to the adaptive filter theory [12] , adaptive linear filter can minimize the mean square error, and its error-signal ratio (SNR −1 ) is close to white noise.…”

Section: Dwba Using Adaptive Linear Prediction For Vbr Video Trafficmentioning

confidence: 99%

Dynamic wavelength and bandwidth allocation using adaptive linear prediction in WDM/TDM ethernet passive optical networks

Guo

2009

J. Shanghai Jiaotong Univ. (Sci.)

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“…Instead of separating the video frames, Xu et al [7] proposes an algorithm which tries to smooth the video traffic by predicting the relative size changes of the same frame in adjacent GOPs [7]. Let xðnÞ be the size of the nth frame in the video sequence.…”

Section: Time Domain Traffic Prediction Algorithmsmentioning

confidence: 99%

“…Based on the work of Adas [6] and Xu et al [7], we propose a method which combines the advantages of both algorithms to reduce short-term traffic variation and smooth the traffic value to be predicted. Instead of predicting video frames directly, the proposed method first separates video sequence into I, P and B subgroups and then predicts the absolute difference between adjacent frames in each subgroup.…”

Section: The Proposed Time Domain Prediction Algorithmmentioning

confidence: 99%

“…It has been widely used in dynamic bandwidth allocation [1][2][3][4]. A number of prediction algorithms have been proposed in the literature, which include neural network approach [1,5], normalized least mean square (NLMS) approach [6,7] and wavelet decomposition approach [4]. These algorithms can be broadly classified into two categories: time domain approaches and wavelet domain approaches.…”

Section: Introductionmentioning

confidence: 99%

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Real time variable bit rate video traffic prediction

Mao

Liu

2006

Int J Communication

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SUMMARYReal time variable bit rate (VBR) video traffic prediction plays an important role in dynamic bandwidth allocation schemes by providing an accurate estimation of the instantaneous bandwidth requirement of VBR video traffic and it has been widely used in dynamic bandwidth allocation. A number of prediction algorithms were proposed in the literature and they can be broadly classified into two categories: time domain approaches and wavelet domain approaches. In this paper, we first present a survey of the existing algorithms in the literature. On the basis of the survey, new algorithms are proposed in the time domain and in the wavelet domain, respectively. Simulations using real VBR video traces are conducted which show that the proposed algorithms achieve better performance than those in the literature.

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Short-term MPEG-4 video traffic prediction using ANFIS

Abdennour

2005

Int. J. Network Mgmt.

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Multimedia traffic and particularly MPEG-coded video streams are growing to be a major traffic component in high-speed networks. Accurate prediction of such traffic enhances the reliable operation and the quality of service of these networks through a more effective bandwidth allocation and better control strategies. However, MPEG video traffic is characterized by a periodic correlation structure, a highly complex bit rate distribution and very noisy streams. Therefore, it is considered an intractable problem. This paper presents a neuro-fuzzy short-term predictor for MPEG-4-coded videos. The predictor is based on the Adaptive Network Fuzzy Inference System (ANFIS) to perform single-step predictions for the I, P and B frames. Short-term predictions are also examined using smoothed signals of the video sequences. The ANFIS prediction results are evaluated using long entertainment and broadcast video sequences and compared to those obtained using a linear predictor. ANFIS is capable of providing accurate prediction and has the added advantage of being simple to design and to implement.

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Adaptive linear prediction of MPEG video traffic

Cited by 24 publications

References 14 publications

Dynamic wavelength and bandwidth allocation using adaptive linear prediction in WDM/TDM ethernet passive optical networks

Dynamic wavelength and bandwidth allocation using adaptive linear prediction in WDM/TDM ethernet passive optical networks

Real time variable bit rate video traffic prediction

Short-term MPEG-4 video traffic prediction using ANFIS

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