Improve Error Resilience Research Articles

Strategic Approaches to AWS Lambda Error Resilience: Insights into Sync and Async Invocation Dynamics

This technical paper focuses on efficient error-handling techniques within Lambda functions and offers helpful insights into connecting AWS Lambda with an Application Load Balancer (ALB). Engineers can find practical solutions in the discussion, including illustrated code snippets and focusing on synchronous and asynchronous invocation types. The article examines the architectural concerns of using an AWS Lambda as the backend for an ALB. With the ALB-to-Lambda architecture in mind, methods for improving error resilience in Lambda functions in sync and async invoke types are discussed. The report also discusses the subtle differences between throttle and error, two vital metrics. Using real-world examples, engineers will get the skills to implement reliable error-handling procedures adapted to various invocation kinds. The insights offered serve as a brief yet thorough reference for maximizing the performance of AWS Lambda behind an ALB, guaranteeing efficient error management, and tackling the particular difficulties brought forth by sync and async invocations. This tool provides engineers with practical approaches that will enable them to build robust serverless applications in the AWS cloud

Error‐Resilient Multi‐view Video Coding Based on End‐to‐End Rate‐Distortion Optimization

Video transmission over packet-switched networks usually suffers from packet losses. The use of the prediction loop in video coding will cause these errors to propagate to subsequent frames, and thus significantly impacts on the received video quality. With the increasing number of cameras to capture the scene, robustly delivering multi-view video over error-prone channels becomes a rather challenging task. A rate-distortion optimization algorithm is proposed to improve error resilience for multi-view video transmission. A recursive model to estimate the end-to-end distortion is developed for multiview video coding, in which the distortion model explicitly takes into consideration the inherent error resilience property of the hierarchical bi-prediction structure. Based on the proposed distortion model, end-to-end rate-distortion optimization criterion is employed to perform coding mode switching. Extensive experimental results demonstrate significant performance gains can be achieved for multi-view video communication against transmission errors.

A Rate–Distortion Optimized Error-Resilient Algorithm for Multi-view Video Coding

In this paper, a new rate---distortion (R---D) optimized error-resilient scheme is proposed to improve error resilience for multi-view video transmission over lossy networks. Based on the study on the characteristics of multi-view video coding and the propagating behavior of channel errors, a recursive model to estimate the end-to-end distortion is first developed, in which the channel-induced distortion takes into consideration both motion and disparity compensation prediction. Then, based on the estimated distortion and the derived total bit rate, R---D optimized motion and disparity estimation are employed to find the reliable motion vector and disparity vector to achieve the optimum trade-off between prediction efficiency and error robustness. Finally, R---D optimization is applied again to perform coding mode decision, which explicitly considers intra, inter and inter-view prediction modes. Extensive experimental results demonstrate significant performance gains can be achieved for multi-view video communications against transmission errors.

Rate-Distortion Optimized Mode Switching for Error-Resilient Multi-View Video Plus Depth Based 3-D Video Coding

In this paper, a rate-distortion optimized coding mode switching scheme is proposed to improve error resilience for multi-view video plus depth (MVD) based 3-D video transmission over lossy networks. First, we derive a new end-to-end distortion model for MVD-based 3-D video transmission. As compared with the previous MVD-based video distortion models in which distortion is measured by only investigating the expected texture video errors and depth errors on the synthesized virtual view, the proposed scheme characterizes both the end-to-end distortions in the rendered virtual view and the coded texture video due to packet losses. Moreover, inter-view error propagation for the texture video and depth map is also considered. Based on the proposed distortion model, an optimal mode decision algorithm is then performed in the texture video and depth map coding process. Experimental results show that the proposed method provides significant improvements in terms of both objective and subjective evaluations.

Efficient Prediction Structures for H.264 Multi View Coding Using Temporal Scalability

Prediction structures with disposable view components based hierarchical coding have been proven to be efficient for H.264 multi view coding. Though these prediction structures along with the QP cascading schemes provide superior compression efficiency when compared to the traditional IBBP coding scheme, the scalability requirements of the bit stream could not be met to the fullest. On the other hand, a fully scalable bit stream, obtained by temporal identifier based hierarchical coding, provides a number of advantages including bit rate adaptations and improved error resilience, but lacks in compression efficiency when compared to the former scheme. In this paper it is proposed to combine the two approaches such that a fully scalable bit stream could be realized with minimal reduction in compression efficiency when compared to state-of-the-art disposable view components based hierarchical coding. Simulation results shows that the proposed method enables full scalability with maximum BDPSNR reduction of only 0.34 dB. A novel method also has been proposed for the identification of identifier for the legacy H.264/AVC base layer packets. Simulation results also show that this enables the scenario where the enhancement views could be extracted at a lower frame rate (1/2nd or 1/4th of base view) with average extraction time for a view component of only 0.38 ms.

Practical distributed video coding in packet lossy channels

Improving error resilience of video communications over packet lossy channels is an important and tough task. We present a framework to optimize the quality of video communications based on distributed video coding (DVC) in practical packet lossy network scenarios. The peculiar characteristics of DVC indeed require a number of adaptations to take full advantage of its intrinsic robustness when dealing with data losses of typical real packet networks. This work proposes a new packetization scheme, an investigation of the best error-correcting codes to use in a noisy environment, a practical rate-allocation mechanism, which minimizes decoder feedback, and an improved side-information generation and reconstruction function. Performance comparisons are presented with respect to a conventional packet video communication using H.264/advanced video coding (AVC). Although currently the H.264/AVC rate-distortion performance in case of no loss is better than state-of-the-art DVC schemes, under practical packet lossy conditions, the proposed techniques provide better performance with respect to an H.264/AVC-based system, especially at high packet loss rates. Thus the error resilience of the proposed DVC scheme is superior to the one provided by H.264/AVC, especially in the case of transmission over packet lossy networks.

High Quality of Service on Video Streaming in P2P Networks Using FST-MDC

Video streaming applications have newly attracted a large number of participants in a distribution network. Traditional client-server based video streaming solutions sustain precious bandwidth provision rate on the server. Recently, several P2P streaming systems have been organized to provide on-demand and live video streaming services on the wireless network at reduced server cost. Peer-to-Peer (P2P) computing is a new pattern to construct disseminated network applications. Typical error control techniques are not very well matched and on the other hand error prone channels has increased greatly for video transmission e.g., over wireless networks and IP. These two facts united together provided the essential motivation for the development of a new set of techniques (error concealment) capable of dealing with transmission errors in video systems. In this paper, we propose an flexible multiple description coding method named as Flexible Spatial-Temporal (FST) which improves error resilience in the sense of frame loss possibilities over independent paths. It introduces combination of both spatial and temporal concealment technique at the receiver and to conceal the lost frames more effectively. Experimental results show that, proposed approach attains reasonable quality of video performance over P2P wireless network.

Joint Temporal and Spatial Error Concealment for Multiple Description Video Coding

Transmission of compressed video signals over error-prone networks exposes the information to losses and errors. To reduce the effects of these losses and errors, this paper presents a joint spatial-temporal estimation method which takes advantages of data correlation in these two domains for better recovery of the lost information. The method is designed for the hybrid multiple description coding which splits video signals along spatial and temporal dimensions. In particular, the proposed method includes fixed and content-adaptive approaches for estimation method selection. The fixed approach selects the estimation method based on description loss cases, while the adaptive approach selects the method according to pixel gradients. The experimental results demonstrate that improved error resilience can be accomplished by the proposed estimation method.

Computation of the Para-Pseudoinverse for Oversampled Filter Banks: Forward and Backward Greville Formulas

Frames and oversampled filter banks have been extensively studied over the past few years due to their increased design freedom and improved error resilience. In frame expansions, the least square signal reconstruction operator is called the <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">dual</i> <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">frame,</i> which can be obtained by choosing the synthesis filter bank as the para-pseudoinverse of the analysis bank. In this paper, we study the computation of the dual frame by exploiting the <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Greville</i> formula, which was originally derived in 1960 to compute the pseudoinverse of a matrix when a new row is appended. Here, we first develop the backward Greville formula to handle the case of row deletion. Based on the forward Greville formula, we then study the computation of para-pseudoinverse for extended filter banks and Laplacian pyramids. Through the backward Greville formula, we investigate the frame-based error resilient transmission over erasure channels. The necessary and sufficient condition for an oversampled filter bank to be robust to one erasure channel is derived. A postfiltering structure is also presented to implement the para-pseudoinverse when the transform coefficients in one subband are completely lost.

Adaptive temporal error concealment scheme for H.264/AVC video decoder

Resilience to channel noise is indispensable for video communication based consumer applications. Temporal error concealment is a kind of decoder-based technique to compensate for transmission errors and is popular in most consumer electronics. In this paper, an adaptive temporal error concealment scheme is proposed based on H.264 video standard to improve error resilience ability for video consumer applications. Mode switching mechanism is devised to flexibly choose appropriate temporal concealment mode. The search range for candidate motion vectors could be adaptively determined by the range of spatially and temporally neighboring motion vectors. Weighted outer boundary distortion function could dynamically select the optimal replacing motion vector for local area. Experiment and comparison with recent error concealment schemes shows that our proposed algorithm could effectively improve received video quality with reduced requirement for decoding time.

Absolute value coding for robust and scalable video coding

Absolute value coding is introduced as a method for significantly reducing temporal drift within a motion compensated predictive video codec in the presence of loss. Drift reduction both improves error resilience and enables scalability by omission of parts of the bit-stream. In conjunction with matching pursuits, the system can be used to provide a displaced frame difference codec using fixed length codewords, which further improves error resilience and facilitates simple bit-stream editing.

Error-resilient pattern classification using a combination of spreading and coding gains

An approach that aims to enhance error resilience in pattern classification problems is proposed. The new approach combines the spread spectrum technique, specifically its selectivity and sensitivity, with error-correcting output codes (ECOC) for pattern classification. This approach combines both the coding gain of ECOC and the spreading gain of the spread spectrum technique to improve error resilience. ECOC is a well-established technique for general purpose pattern classification, which reduces the multi-class learning problem to an ensemble of two-class problems and uses special codewords to improve the error resilience of pattern classification. The direct sequence code division multiple access (DS-CDMA) technique is a spread spectrum technique that provides high user selectivity and high signal detection sensitivity, resulting in a reliable connection through a noisy radio communication channel shared by multiple users. Using DS-CDMA to spread the codeword, assigned to each pattern class by the ECOC technique, gives codes with coding properties that enable better correction of classification errors than ECOC alone. Results of performance assessment experiments show that the use of DS-CDMA alongside ECOC boosts error-resilience significantly, by yielding better classification accuracy than ECOC by itself.

Refreshment need metrics for improved shape and texture object-based resilient video coding

Video encoders may use several techniques to improve error resilience. In particular, for video encoders that rely on predictive (inter) coding to remove temporal redundancy, intra coding refreshment is especially useful to stop error propagation when errors occur in the transmission or storage of the coded streams, which can cause the decoded quality to decay very rapidly. In the context of object-based video coding, the video encoder can apply intra coding refreshment to both the shape and the texture data. In this paper, shape refreshment need and texture refreshment need metrics are proposed which can be used by object-based video encoders, notably MPEG-4 video encoders, to determine when the shape and the texture of the various video objects in the scene should be refreshed in order to improve the decoded video quality, e.g., for a given bitrate.