Dynamic bandwidth allocation in ATM networks

Includes bibliographical references.This thesis investigates bandwidth allocation methodologies to transport new emerging bursty traffic types in ATM networks. However, existing ATM traffic management solutions are not readily able to handle the inevitable problem of congestion as result of the bursty traffic from the new emerging services. This research basically addresses bandwidth allocation issues for bursty traffic by proposing and exploring the concept of dynamic bandwidth allocation and comparing it to the traditional static bandwidth allocation schemes

Slight-Delay Shaped Variable Bit Rate (SD-SVBR) Technique for Video Transmission

The aim of this thesis is to present a new shaped Variable Bit Rate (VBR) for video transmission, which plays a crucial role in delivering video traffic over the Internet. This is due to the surge of video media applications over the Internet and the video typically has the characteristic of a highly bursty traffic, which leads to the Internet bandwidth fluctuation. This new shaped algorithm, referred to as Slight Delay - Shaped Variable Bit Rate (SD-SVBR), is aimed at controlling the video rate for video application transmission. It is designed based on the Shaped VBR (SVBR) algorithm and was implemented in the Network Simulator 2 (ns-2). SVBR algorithm is devised for real-time video applications and it has several limitations and weaknesses due to its embedded estimation or prediction processes. SVBR faces several problems, such as the occurrence of unwanted sharp decrease in data rate, buffer overflow, the existence of a low data rate, and the generation of a cyclical negative fluctuation. The new algorithm is capable of producing a high data rate and at the same time a better quantization parameter (QP) stability video sequence. In addition, the data rate is shaped efficiently to prevent unwanted sharp increment or decrement, and to avoid buffer overflow. To achieve the aim, SD-SVBR has three strategies, which are processing the next Group of Picture (GoP) video sequence and obtaining the QP-to-data rate list, dimensioning the data rate to a higher utilization of the leaky-bucket, and implementing a QP smoothing method by carefully measuring the effects of following the previous QP value. However, this algorithm has to be combined with a network feedback algorithm to produce a better overall video rate control. A combination of several video clips, which consisted of a varied video rate, has been used for the purpose of evaluating SD-SVBR performance. The results showed that SD-SVBR gains an impressive overall Peak Signal-to-Noise Ratio (PSNR) value. In addition, in almost all cases, it gains a high video rate but without buffer overflow, utilizes the buffer well, and interestingly, it is still able to obtain smoother QP fluctuation

Layer-based coding, smoothing, and scheduling of low-bit-rate video for teleconferencing over tactical ATM networks

This work investigates issues related to distribution of low bit rate video within the context of a teleconferencing application deployed over a tactical ATM network. The main objective is to develop mechanisms that support transmission of low bit rate video streams as a series of scalable layers that progressively improve quality. The hierarchical nature of the layered video stream is actively exploited along the transmission path from the sender to the recipients to facilitate transmission. A new layered coder design tailored to video teleconferencing in the tactical environment is proposed. Macroblocks selected due to scene motion are layered via subband decomposition using the fast Haar transform. A generalized layering scheme groups the subbands to form an arbitrary number of layers. As a layering scheme suitable for low motion video is unsuitable for static slides, the coder adapts the layering scheme to the video content. A suboptimal rate control mechanism that reduces the kappa dimensional rate distortion problem resulting from the use of multiple quantizers tailored to each layer to a 1 dimensional problem by creating a single rate distortion curve for the coder in terms of a suboptimal set of kappa dimensional quantizer vectors is investigated. Rate control is thus simplified into a table lookup of a codebook containing the suboptimal quantizer vectors. The rate controller is ideal for real time video and limits fluctuations in the bit stream with no corresponding visible fluctuations in perceptual quality. A traffic smoother prior to network entry is developed to increase queuing and scheduler efficiency. Three levels of smoothing are studied: frame, layer, and cell interarrival. Frame level smoothing occurs via rate control at the application. Interleaving and cell interarrival smoothing are accomplished using a leaky bucket mechanism inserted prior to the adaptation layer or within the adaptation layerhttp://www.archive.org/details/layerbasedcoding00parkLieutenant Commander, United States NavyApproved for public release; distribution is unlimited

Error resilience and concealment techniques for high-efficiency video coding

This thesis investigates the problem of robust coding and error concealment in High Efficiency Video Coding (HEVC). After a review of the current state of the art, a simulation study about error robustness, revealed that the HEVC has weak protection against network losses with significant impact on video quality degradation. Based on this evidence, the first contribution of this work is a new method to reduce the temporal dependencies between motion vectors, by improving the decoded video quality without compromising the compression efficiency. The second contribution of this thesis is a two-stage approach for reducing the mismatch of temporal predictions in case of video streams received with errors or lost data. At the encoding stage, the reference pictures are dynamically distributed based on a constrained Lagrangian rate-distortion optimization to reduce the number of predictions from a single reference. At the streaming stage, a prioritization algorithm, based on spatial dependencies, selects a reduced set of motion vectors to be transmitted, as side information, to reduce mismatched motion predictions at the decoder. The problem of error concealment-aware video coding is also investigated to enhance the overall error robustness. A new approach based on scalable coding and optimally error concealment selection is proposed, where the optimal error concealment modes are found by simulating transmission losses, followed by a saliency-weighted optimisation. Moreover, recovery residual information is encoded using a rate-controlled enhancement layer. Both are transmitted to the decoder to be used in case of data loss. Finally, an adaptive error resilience scheme is proposed to dynamically predict the video stream that achieves the highest decoded quality for a particular loss case. A neural network selects among the various video streams, encoded with different levels of compression efficiency and error protection, based on information from the video signal, the coded stream and the transmission network. Overall, the new robust video coding methods investigated in this thesis yield consistent quality gains in comparison with other existing methods and also the ones implemented in the HEVC reference software. Furthermore, the trade-off between coding efficiency and error robustness is also better in the proposed methods

Temporal View Synthesis of Dynamic Scenes through 3D Object Motion Estimation with Multi-Plane Images

The challenge of graphically rendering high frame-rate videos on low compute devices can be addressed through periodic prediction of future frames to enhance the user experience in virtual reality applications. This is studied through the problem of temporal view synthesis (TVS), where the goal is to predict the next frames of a video given the previous frames and the head poses of the previous and the next frames. In this work, we consider the TVS of dynamic scenes in which both the user and objects are moving. We design a framework that decouples the motion into user and object motion to effectively use the available user motion while predicting the next frames. We predict the motion of objects by isolating and estimating the 3D object motion in the past frames and then extrapolating it. We employ multi-plane images (MPI) as a 3D representation of the scenes and model the object motion as the 3D displacement between the corresponding points in the MPI representation. In order to handle the sparsity in MPIs while estimating the motion, we incorporate partial convolutions and masked correlation layers to estimate corresponding points. The predicted object motion is then integrated with the given user or camera motion to generate the next frame. Using a disocclusion infilling module, we synthesize the regions uncovered due to the camera and object motion. We develop a new synthetic dataset for TVS of dynamic scenes consisting of 800 videos at full HD resolution. We show through experiments on our dataset and the MPI Sintel dataset that our model outperforms all the competing methods in the literature.Comment: To appear in ISMAR 2022; Project website: https://nagabhushansn95.github.io/publications/2022/DeCOMPnet.htm

Efficient and Effective Schemes for Streaming Media Delivery

The rapid expansion of the Internet and the increasingly wide deployment of wireless networks provide opportunities to deliver streaming media content to users at anywhere, anytime. To ensure good user experience, it is important to battle adversary effects, such as delay, loss and jitter. In this thesis, we first study efficient loss recovery schemes, which require pure XOR operations. In particular, we propose a novel scheme capable of recovering up to 3 packet losses, and it has the lowest complexity among all known schemes. We also propose an efficient algorithm for array codes decoding, which achieves significant throughput gain and energy savings over conventional codes. We believe these schemes are applicable to streaming applications, especially in wireless environments. We then study quality adaptation schemes for client buffer management. Our control-theoretic approach results in an efficient online rate control algorithm with analytically tractable performance. Extensive experimental results show that three goals are achieved: fast startup, continuous playback in the face of severe congestion, and maximal quality and smoothness over the entire streaming session. The scheme is later extended to streaming with limited quality levels, which is then directly applicable to existing systems

Low-complexity video coding for receiver-driven layered multicast

In recent years, the “Internet Multicast Backbone,” or MBone, has risen from a small, research curiosity to a large- scale and widely used communications infrastructure. A driving force behind this growth was the development of multipoint audio, video, and shared whiteboard conferencing applications. Because these real-time media are transmitted at a uniform rate to all of the receivers in the network, a source must either run at the bottleneck rate or overload portions of its multicast distribution tree. We overcome this limitation by moving the burden of rate adaptation from the source to the receivers with a scheme we call receiver-driven layered multicast, or RLM. In RLM, a source distributes a hierarchical signal by striping the different layers across multiple multicast groups, and receivers adjust their reception rate by simply joining and leaving multicast groups. In this paper, we describe a layered video compression algorithm which, when combined with RLM, provides a comprehensive solution for scalable multicast video transmission in heterogeneous networks. In addition to a layered representation, our coder has low complexity (admitting an effi- cient software implementation) and high loss resilience (admitting robust operation in loosely controlled environments like the Inter- net). Even with these constraints, our hybrid DCT/wavelet-based coder exhibits good compression performance. It outperforms all publicly available Internet video codecs while maintaining comparable run-time performance. We have implemented our coder in a “real” application—the UCB/LBL videoconferencing tool vic. Unlike previous work on layered video compression and transmission, we have built a fully operational system that is currently being deployed on a very large scale over the MBone