120 research outputs found

    Flow Level QoE of Video Streaming in Wireless Networks

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    The Quality of Experience (QoE) of streaming service is often degraded by frequent playback interruptions. To mitigate the interruptions, the media player prefetches streaming contents before starting playback, at a cost of delay. We study the QoE of streaming from the perspective of flow dynamics. First, a framework is developed for QoE when streaming users join the network randomly and leave after downloading completion. We compute the distribution of prefetching delay using partial differential equations (PDEs), and the probability generating function of playout buffer starvations using ordinary differential equations (ODEs) for CBR streaming. Second, we extend our framework to characterize the throughput variation caused by opportunistic scheduling at the base station, and the playback variation of VBR streaming. Our study reveals that the flow dynamics is the fundamental reason of playback starvation. The QoE of streaming service is dominated by the first moments such as the average throughput of opportunistic scheduling and the mean playback rate. While the variances of throughput and playback rate have very limited impact on starvation behavior.Comment: 14 page

    Supporting real time video over ATM networks

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    Includes bibliographical references.In this project, we propose and evaluate an approach to delimit and tag such independent video slice at the ATM layer for early discard. This involves the use of a tag cell differentiated from the rest of the data by its PTI value and a modified tag switch to facilitate the selective discarding of affected cells within each video slice as opposed to dropping of cells at random from multiple video frames

    The application of forward error correction techniques in wireless ATM

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    Bibliography: pages 116-121.The possibility of providing wireless access to an ATM network promises nomadic users a communication tool of unparalleled power and flexibility. Unfortunately, the physical realization of a wireless A TM system is fraught with technical difficulties, not the least of which is the problem of supporting a traditional ATM protocol over a non-benign wireless link. The objective of this thesis, titled "The Application of Forward Error Correction Techniques in Wireless ATM' is to examine the feasibility of using forward error correction techniques to improve the perceived channel characteristics to the extent that the channel becomes transparent to the higher layers and allows the use of an unmodified A TM protocol over the channel. In the course of the investigation that this dissertation describes, three possible error control strategies were suggested for implementation in a generic wireless channel. These schemes used a combination of forward error correction coding schemes, automatic repeat request schemes and interleavers to combat the impact of bit errors on the performance of the link. The following error control strategies were considered : 1. A stand alone fixed rate Reed-Solomon encoder/decoder with automatic repeat request. 2. A concatenated Reed-Solomon, convolution encoder/decoder with automatic request and convolution interleaving for the convolution codec. 3. A dynamic rate encoder/decoder using either a concatenated Reed-Solomon, convolution scheme or a Reed-Solomon only scheme with variable length Reed-Solomon words

    A quantitative comparison of multiple access control protocols for wireless ATM

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    The multiple access control (MAC) problem in a wireless network has intrigued researchers for years. For a broad-band wireless network such as wireless ATM, an effective MAC protocol is very much desired because efficient allocation of channel bandwidth is imperative in accommodating a large user population with satisfactory quality of service. Indeed, MAC protocols for a wireless ATM network in which user traffic requirements are highly heterogeneous (classified into CBR, VBR, and ABR), are even more intricate to design. Considerable research efforts expended in tackling the problem have resulted in a myriad of MAC protocols. While each protocol is individually shown to be effective by the respective designers, it is unclear how these different protocols compare against each other on a unified basis. In this paper, we quantitatively compare seven recently proposed TDMA-based MAC protocols for integrated wireless data and voice services. We first propose a taxonomy of TDMA-based protocols, from which we carefully select seven protocols, namely SCAMA, DTDMA/VR, DTDMA/PR, DQRUMA, DPRMA, DSA++, and PRMA/DA, such that they are devised based on rather orthogonal design philosophies. The objective of our comparison is to highlight the merits and demerits of different protocol designs.published_or_final_versio

    Video traffic modeling and delivery

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    Video is becoming a major component of the network traffic, and thus there has been a great interest to model video traffic. It is known that video traffic possesses short range dependence (SRD) and long range dependence (LRD) properties, which can drastically affect network performance. By decomposing a video sequence into three parts, according to its motion activity, Markov-modulated self-similar process model is first proposed to capture autocorrelation function (ACF) characteristics of MPEG video traffic. Furthermore, generalized Beta distribution is proposed to model the probability density functions (PDFs) of MPEG video traffic. It is observed that the ACF of MPEG video traffic fluctuates around three envelopes, reflecting the fact that different coding methods reduce the data dependency by different amount. This observation has led to a more accurate model, structurally modulated self-similar process model, which captures the ACF of the traffic, both SRD and LRD, by exploiting the MPEG structure. This model is subsequently simplified by simply modulating three self-similar processes, resulting in a much simpler model having the same accuracy as the structurally modulated self-similar process model. To justify the validity of the proposed models for video transmission, the cell loss ratios (CLRs) of a server with a limited buffer size driven by the empirical trace are compared to those driven by the proposed models. The differences are within one order, which are hardly achievable by other models, even for the case of JPEG video traffic. In the second part of this dissertation, two dynamic bandwidth allocation algorithms are proposed for pre-recorded and real-time video delivery, respectively. One is based on scene change identification, and the other is based on frame differences. The proposed algorithms can increase the bandwidth utilization by a factor of two to five, as compared to the constant bit rate (CBR) service using peak rate assignment

    Application of learning algorithms to traffic management in integrated services networks.

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    SIGLEAvailable from British Library Document Supply Centre-DSC:DXN027131 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

    A new approach for asynchronous distributed rate control of elastic sessions in integrated packet networks

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    We develop a new class of asynchronous distributed algorithms for the explicit rate control of elastic sessions in an integrated packet network. Sessions can request for minimum guaranteed rate allocations (e.g., minimum cell rates in the ATM context), and, under this constraint, we seek to allocate the max-min fair rates to the sessions. We capture the integrated network context by permitting the link bandwidths available to elastic sessions to be stochastically time varying. The available capacity of each link is viewed as some statistic of this stochastic process [e.g., a fraction of the mean, or a large deviations-based equivalent service capacity (ESC)]. The ESC is obtained so as to satisfy an overflow probability constraint on the buffer length. For fixed available capacity at each link, we show that the vector of max-min fair rates can be computed from the root of a certain vector equation. A distributed asynchronous stochastic approximation technique is then used to develop a provably convergent distributed algorithm for obtaining the root of the equation, even when the link flows and the available capacities are obtained from on-line measurements. The switch algorithm does not require per connection monitoring, nor does it require per connection marking of control packets. A virtual buffer based approach for on-line estimation of the ESC is utilized. We also propose techniques for handling large variations in the available capacity owing to the arrivals or departures of CBR/VBR sessions. Finally, simulation results are provided to demonstrate the performance of this class of algorithms in the local and wide area network context

    Some aspects of traffic control and performance evaluation of ATM networks

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    The emerging high-speed Asynchronous Transfer Mode (ATM) networks are expected to integrate through statistical multiplexing large numbers of traffic sources having a broad range of statistical characteristics and different Quality of Service (QOS) requirements. To achieve high utilisation of network resources while maintaining the QOS, efficient traffic management strategies have to be developed. This thesis considers the problem of traffic control for ATM networks. The thesis studies the application of neural networks to various ATM traffic control issues such as feedback congestion control, traffic characterization, bandwidth estimation, and Call Admission Control (CAC). A novel adaptive congestion control approach based on a neural network that uses reinforcement learning is developed. It is shown that the neural controller is very effective in providing general QOS control. A Finite Impulse Response (FIR) neural network is proposed to adaptively predict the traffic arrival process by learning the relationship between the past and future traffic variations. On the basis of this prediction, a feedback flow control scheme at input access nodes of the network is presented. Simulation results demonstrate significant performance improvement over conventional control mechanisms. In addition, an accurate yet computationally efficient approach to effective bandwidth estimation for multiplexed connections is investigated. In this method, a feed forward neural network is employed to model the nonlinear relationship between the effective bandwidth and the traffic situations and a QOS measure. Applications of this approach to admission control, bandwidth allocation and dynamic routing are also discussed. A detailed investigation has indicated that CAC schemes based on effective bandwidth approximation can be very conservative and prevent optimal use of network resources. A modified effective bandwidth CAC approach is therefore proposed to overcome the drawback of conventional methods. Considering statistical multiplexing between traffic sources, we directly calculate the effective bandwidth of the aggregate traffic which is modelled by a two-state Markov modulated Poisson process via matching four important statistics. We use the theory of large deviations to provide a unified description of effective bandwidths for various traffic sources and the associated ATM multiplexer queueing performance approximations, illustrating their strengths and limitations. In addition, a more accurate estimation method for ATM QOS parameters based on the Bahadur-Rao theorem is proposed, which is a refinement of the original effective bandwidth approximation and can lead to higher link utilisation
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