Cycle modulated sources and their correlation structure

Variable Bit Rate (VBR) video traffic modeling is one of the most important challenges in setting up the communication networks. It is applicable to the efficient designing and using of the networks. There are some solutions to the problem of VBR Video traffic modeling. These solutions are divided in to two categories: statistical modeling and deterministic modeling. In this paper, we propose a new deterministic model based on the nonlinear mapping characteristic of fuzzy systems, implemented using a Generalized Regression Neural Network (GRNN). This model is tested with prediction of next 5, 10 and 20 frames of I, P and B frames of the desired movie, using 100 current frames. The model generated data is examined by the matching of autocorrelation function and histogram. This model can regenerate the ACF and histogram of video traces, in order of 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-3</sup> in error.

When a Banyan switch is used to switch variable bit rate (VBR) video, some video packets may not be switched before their deadlines because the VBR video sources may temporarily generate heavy traffic or they only generate moderate traffic but some video packets encounter internal blocking in the switch. Therefore, some video packets may be discarded. We determine the condition of packet loss and then derive the packet loss probability. Based on this result, we perform admission control to determine whether a given video session can be admitted while the resulting packet loss probability is still small enough to guarantee a good image quality.

The transmission of variable-bit rate (VBR) video over ATM is a challenge because it combines the requirement for on-time data delivery with a bursty traffic characteristic. We focus on the role of ATM endsystems in the transmission of VBR video and examine how traffic shaping in the sender reduces the burstiness of the video stream and therefore the network resource requirements, both for video encoded in real-time and stored video. Shapers based on multiple leaky buckets are popular because they are particularly simple to implement. We present basic results on their buffer requirements and provide new, tighter bounds for their output traffic, enabling efficient resource allocation as well as a significant reduction in the number of leaky buckets required. We extend the basic shaping mechanism to provide efficient shaping for stored video. Finally we compare empirically the performance of multiple leaky bucket shaping with an optimal algorithm for MPEG-1 encoded video and find under realistic conditions near-optimal performance with very few leaky buckets.

A simple mathematical treatment was derived to predict the probability of frame loss for four different models of variable bit rate (VBR) video coding such that access control into a high speed network could be enforced effectively. To maintain a level of quality-of-service (QOS) in broadband ISDN, access to the network is controlled by an edge node. To do that, the node processor must quickly calculate the effect of the video call establishment. If the QOS can not be guaranteed, the call should be blocked. This paper presents some results of signal loss due to multiplexing of more than one VBR video signals. Simple simulation techniques were used for the purpose. Modification of the Markov process was done to model several types video signals. >

This paper is concerned with transmission of a moving picture expert group (MPEG) video stream over a Bluetooth channel, using an adaptive neuro-fuzzy technique. MPEG variable bit rate (VBR) video sources over a network generally experience long delay and unacceptable data loss, due to high variations in bit rate. Furthermore, transmission rate could be unpredictable in a Bluetooth network due to interferences by other wireless devices or general Bluetooth channel noises. Subsequently, it is almost impossible to transmit VBR data sources over Bluetooth without excessive delay or data loss. In this work, an adaptive scheme is introduced so that the controller may adjust itself to the current state of the system under control. This paper utilizes a traffic-shaping buffer to prevent excessive back-to-back transmissions of MPEG VBR data sources. A novel adaptive neuro-fuzzy scheme regulates the output rate of the buffer to ensure that the video stream from the host conforms to the traffic conditions of the Bluetooth channel during the transmission period. The computer simulation results show that the use of the neuro-fuzzy controller reduces excessive delay and data loss at the host-controller-interface, as compared with a conventional VBR video transmission and a rule-based fuzzy controller (RBF1) in Bluetooth

The error and delay performance of variable bit rate (VBR) video transmission over non-ideal channels is examined using equalization schemes. The temporal correlation features of the fading signal and the source video are modeled using finite state Markov chains. The source and training signals are multiplexed using a time slotted multiple access scheme. For slow-fading channels, the characteristic time-scale of the fade durations, the step-size parameter of the LMS equalizer training algorithm, and the number of training sequences allocated per time slot are found to jointly influence error performance. Simulation results show that the proposed channel access scheme can lead to an order of magnitude decrease in the bit error ratio if the combination of training overhead and step-size parameter are chosen judiciously with respect to the fading time-scale. In addition, the multiplexing efficiency of VBR encoded video is shown to be useful for limiting the channel access delays when the training overhead is increased.

It has been shown that Variable Bit Rate (VBR) video exhibits long-range dependence characteristics. Several models have been proposed to synthesize traces whose autocorrelation match that of the video traffic traces. Given the relationship between self-similarity and long- range dependence, we investigate the application of discrete-time linear scale invariant systems provided by Zhao and Rao to modeling VBR video traffic. This formulation, called a DLSI system, was derived using a continuous dilation operator in discrete-time as a direct analog of the continuous-time linear scale-invariant system formulation of Wornell and differs from other approaches such as wavelet based construction. While simulations had shown that DLSI systems were capable of generating self- similar data such as those found in network traffic, questions regarding their long-range behavior remained. Answers to these questions are dealt in this paper. We present an alternative modeling technique to model VBR video traffic using DLSI system. The proposed model has a fractional pole-zero structure and provides a good model for long-range dependent and self-similar time series. The behavioral pattern of the fractional pole-zero filter for a range of the Hurst parameter is also shown. The time-domain characteristics of the filter are analyzed using power series approximations. Comparison of output autocorrelation function (ACF) to those of the video trace ACF is made. We conclude that some samples of video data are indeed better modeled by the LSI models than the conventional models such as Markovian and Long-range dependent models.

Performance evaluation methods that have been used so far failed to capture the real characteristics of network traffic. This is especially true when the service times are general such as the variable bit rate (VBR) video, which is proven to be self-similar. In the paper, diffusion approximation methods are proposed to analyse a dynamic scheduler for self-similar VBR video traffic in asynchronous transfer mode (ATM) networks. The proposed scheme employs a coupled queueing system that has been used extensively in the modelling of computer and communication systems. Diffusion approximations methods are used to decouple a queueing system which represents an ATM network node into separate G/G/1 queues. Real MPEG video traces are used in the discrete event simulation. Results are compared with the approximation, and are found to work very well under different traffic conditions.

A study of the burstiness of combined MPEG video and audio bitstreams

In this paper, a practical dynamic resource allocation scheme for real-time variable bit rate (VBR) video transmission is investigated. This scheme uses time-domain adaptive linear prediction, instead of the conventional size prediction of I-, P- and B- frames, to forecast future bandwidth requirement in time. Media delivery index (MDI) is used here as QoS measurement and complementary reference for adjustment. Besides, considering that the practical multi-user application may arouse adjustment collision, an adjustment priorities classified strategy based on the user-level classifications is put forward. Last, a test-bed based on the proposed scheme is constructed and the experimental results show that the bandwidth effective utilization has increased by 20%-60% compared to a fixed service rate with QoS guaranteed and no collisions.

In the past few years, video streaming over cellular networks has become increasingly popular due to which managing end-user Quality of Experience (QoE) has become a crucial problem. We consider the problem of variable bit rate (VBR) video streaming over heterogeneous cellular networks (HetNets). We address this problem as a joint assignment and scheduling problem and design QoE-aware greedy algorithms to solve it. The greedy assignment algorithm links users to femtocells for downloading the videos from, and the greedy scheduling algorithm fairly allocates time slots to the users assigned to a specific femtocell. Our experiments on real-world 4G LTE wireless connectivity and VBR video traces show the superior performance of our algorithm.

Rate Control is an important component in a video encoder for date storage or real-time visual communication. In this paper, we will discuss the rate control in MPEG encoder for real-time video communication over Variable Bit Rate (VBR) channel. In interactive video communication, the video transmission is subject to both channel rate constraints and end-to-end delay constraints. Our goal in this paper is to modify the rate control in MPEG-2 encoder and satisfy the rate constraints, and study how to improve the video quality in the scenario of VBR transmission. Here, we employ Leaky- Bucket to describe the traffic parameters and monitor the encoder's output. Depending on the Rate-distortion models developed by us, we present a rate control algorithm to achieve almost uniform distortion both within a frame and between frames in a scene. With adaptive rate-distortion models and additional function of scene detecting, our method can robustly deal with scenes of different statistical characteristics. Comparing to MPEG2 TM5, in real time video communication, we could keep the constant buffer delay while maintain the decoded image quality stable. Furthermore, the bit allocation in our algorithm is more reasonable and controllable. Therefore, our method realized the advantages that advanced by VBR video communication, such as small end-to-end delay, consistent image quality and high channel efficiency.

In this paper we consider the transmission of stored video from a server to a client for medical applications such as, Telemonitoring, to optimize medical quality of service (m-QoS) and to examine how the client buffer space can be used efficiently and effectively towards reducing the rate variability of the compressed variable bit rate (VBR) video. Three basic results are presented. First, we show how to obtain the greatest possible reduction in rate variability when sending stored video to client with a given buffer size. Second, how to reduce high peak data rate of compressed VBR video when a patient is moving/walking very fast in hospital. Third, we evaluate the impact of optimal smoothing algorithm on the network parameters such as, peak-to-mean ratio, standard deviation, delay, jitter, average delay and average jitter to optimize the m-QoS. To resolve these all problems we used optimal smoothing algorithm and show its performance over a set of long MPEG-4 encoded video traces. Simulation results show that m-QoS is optimized by minimizing network metrics.

Video traffic is expected to become increasingly important with the large scale deployment of broadband ISDN. In the literature, it is suggested that smoothing variable bit rate (VBR) video traffic1,2 before transmitting it onto the network would help reduce the probability of cell loss. In this paper we show why deterministic smoothing at the source approximates the minimum achievable loss over the network end‐to‐end of all possible smoothing schemes. Furthermore, we develop a powerful yet simple analytical technique that can efficiently calculate the loss probability at any point in a network carrying video traffic. We validate our analytical results using traces of actual video segments. The results can be used for admission control and traffic management. We find that in the case of highly correlated traffic such as motion JPEG video, the way to control loss is to ensure that the fraction of time the arrival process exceeds the service process is small. We also find that for such sources increasing the buffer size only marginally decreases the loss.

This paper is concerned with an intelligent application of Moving Picture Expert Group (MPEG) video transmission in a Bluetooth link. MPEG Variable Bit Rate (VBR) video is data hungry and results in excessive data loss and time delay over wireless networks. In a Bluetooth channel transmission rate is unpredictable as result of interferences by channel noises or other close by wireless devices. Therefore, it is difficult to transmit MPEG VBR video in Bluetooth without data loss and/or time delay. A buffer entitled ‘traffic regulating buffer’ is introduced before the Bluetooth protocol stack to prevent excessive overflow of MPEG video data over the network. Two novel neural fuzzy schemes are presented in this paper to monitor the traffic regulating buffer input and output rates, in order to ensure the video stream conforms to the traffic conditions of Bluetooth. The computer simulation results demonstrate that the two supervised neural fuzzy schemes reduce standard deviation and data loss, when compared with a traditional MPEG VBR video transmission over Bluetooth.KeywordsVideo TransmissionInternal Model ControlGeneral Packet Radio ServiceAdaptive Neural Fuzzy Inference SystemMove Picture Expert GroupThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.