Error Recovery Performance Research Articles

Efficient Mobile Video Streaming via Context-Aware RaptorQ-Based Unequal Error Protection

Mobile video streaming systems typically apply the forward error correction (FEC) at the application layer to cope with packet-level transmission errors, which complements the bit-level correction mechanisms at the physical layer. However, most existing works fail to exploit the block-level dependencies in both intra and interframe coding modes of a single-layer compressed video, and thus are less efficient for the prevailing H.264/AVC and/or H.265/HEVC compatible single-layer video application. To this end, we propose a low-complexity FEC, i.e., context-aware RaptorQ (CA-RQ) with unequal error protection (UEP), to improve the error recovery performance of the single-layer mobile video streaming, through incorporating the block-level dependencies in the compressed video data. We use a packet-level video transmission distortion model that considers the dependencies in both spatial and temporal domains, to quantify the importance of video packets within a group of pictures (GoP). The compressed video packets are categorized and grouped into several classes according to their importance to construct the CA-RQ code with the UEP property. We provide a theoretical analysis on redundancy allocation bounds to demonstrate the superior performance of proposed CA-RQ over the standard RaptorQ code. In the meantime, extensive simulations have shown that our scheme not only offers much better subjective visual quality with less than 50% additional redundant symbols as compared to the Macroblock-Based UEP (MB-UEP) scheme, but also outperforms the MB-UEP and classical equal error protection (EEP)-based schemes, by a 0.45% $\sim$ 5.71% and 0.94% $\sim$ 6.78% margin, respectively, in reconstructed quality evaluated using the structural similarity (SSIM) index, across a reasonable range of redundancy proportions.

Tilt-Prioritized Quadrocopter Attitude Control

This paper presents an attitude tracking control law and control allocation strategy for quadrocopters which prioritizes the vehicle’s ability to achieve a desired translational acceleration. The quadrocopter’s attitude error is split into a reduced attitude error, which describes the misalignment of the thrust direction, and a yaw error, which describes the orientation error about the thrust direction. A model-based proportional–derivative control law is derived, where the proportional action is in terms of the reduced attitude and yaw errors, and the derivative action is in terms of the quadrocopter’s angular velocity error. Almost global asymptotic convergence of the reduced attitude error is established, and the convergence of the yaw error is proven. It is further shown that the attitude control law decouples the reduced attitude error dynamics from the yaw error dynamics. A control allocation strategy is derived which exploits the decoupling in order to prioritize the correction of the reduced attitude over the yaw error. The proposed control strategy is computationally lightweight and therefore well-suited to run on board quadrocopters at high rates. Experimental results demonstrate improved error recovery and position tracking performance.

A Random Linear Network Coding Accelerator in a 2.4GHz Transmitter for IoT Applications

Random linear network coding (RLNC) is an emerging coding technique, which can provide several advantages in wireless networks, such as throughput gains, increased data robustness, and better utilization of network resources. In this paper, we present the first custom VLSI implementation of RLNC, integrated with an ultralow-power 2.4-GHz transmitter. We examine its energy efficiency and error recovery performance in the context of Internet of Things applications, and we perform experiments quantifying its benefits when it operates separately and jointly with physical layer forward error correction (FEC) codes, as a joint channel and network coding scheme. The chip is fabricated in a 65-nm CMOS process, occupies $2 \times 1.3 ~{\mathrm{ m}}{\mathrm{ m}}^{2}$ and consumes 580 pJ/bit for processing and transmitting data at 1 Mbps. The digital packet processor and encoder occupies $200\times 200 ~\mu {\mathrm{ m}}^{2}$ , consists of an on-chip memory, a multi-rate convolutional encoder, and a RLNC accelerator with configurable redundancy, and consumes $15\mu \text{W}$ , operating at 0.4 V. For improved spectral efficiency, an on-chip pulse shaping filter is implemented, reducing side lobes by 28 dB while consuming $15\mu \text{W}$ . According to our over-the-air experiments, RLNC can provide an effective SNR improvement of 5.6 dB when combined with FEC rate 1/2, and 3.4 dB without FEC, at a packet error rate of $10^{-2}$ .

Communication-Efficient Decentralized Sparse Bayesian Learning of Joint Sparse Signals

We consider the problem of decentralized estimation of multiple joint sparse vectors by a network of nodes from locally acquired noisy and underdetermined linear measurements, when the cost of communication between the nodes is at a premium. We propose an iterative, decentralized Bayesian algorithm called fusion-based distributed sparse Bayesian learning (FB-DSBL) in which the nodes collaborate by exchanging highly compressed messages to learn a common joint sparsity inducing signal prior. The learnt signal prior is subsequently used by each node to compute the maximum a posteriori probability estimate of its respective sparse vector. Since the internode communication cost is expensive, the size of the messages exchanged between nodes is reduced substantially by exchanging only those local signal prior parameters which are associated with the nonzero support detected via multiple composite log-likelihood ratio tests. The average message size is empirically shown to be proportional to the information rate of the unknown vectors. The proposed sparse Bayesian learning (SBL)-based distributed algorithm allows nodes to exploit the underlying joint sparsity of the signals. In turn, this enables the nodes to recover sparse vectors with significantly lower number of measurements compared to the standalone SBL algorithm. The proposed algorithm is interpreted as a degenerate case of a distributed consensus-based stochastic approximation algorithm for finding a fixed point of a function, and its generalized version with Robbins–Monro-type iterations is also developed. Using Monte Carlo simulations, we demonstrate that the proposed FB-DSBL has superior mean squared error and support recovery performance compared to the existing decentralized algorithms with similar or higher communication complexity.

Error Recovery Performance

This article introduces the concept of error recovery performance, followed by the development and validation of an instrument to measure it. The first objective of this article is to broaden the current concept of service recovery to be relevant to the back-of-house operations. The second objective is to examine the influence of leader behavioral integrity (BI) on error recovery performance. Moreover, the study examines the mediating effect of job satisfaction between BI and error recovery performance. Finally, the study links error management performance with work-unit effectiveness. Data for Study 1 were collected from 369 hotel employees in Turkey. The same relationships were tested again in Study 2 to validate the findings of Study 1 with a different sample. Data for Study 2 were collected from 33 departmental managers from the same hotels. Linear regression analysis was used to test the direct effects. The mediating effects were tested using the mediation test suggested by Preacher and Hayes. In addition, in Study 2, general managers of the hotels were asked to rate the effectiveness of each manager and their respective department. Results from Study 1 indicate that BI drives error recovery performance, and this impact is mediated by employee job satisfaction. Results of Study 2 confirm this model and finds further that managers’ self-rated error recovery performance was associated with their general managers’ assessment of their deliverables and of their department’s overall performance.

Physical layer DVB‐SH performance prediction based on mutual information

SUMMARYDigital Video Broadcasting‐Satellite Handled (DVB‐SH) is a hybrid satellite terrestrial broadcasting standard dedicated to provide video or audio services for handheld terminals. On the satellite part, this standard can make use of interleaving mechanisms to mitigate the effects of the Land Mobile Satellite channel. As a result, these mechanisms enable the in‐time distribution of a codeword over a duration ranging from 100 ms to about 30 s, depending on their parameters. This mechanism significantly improves the error recovery performance of the code; however in the literature, a theoretical evaluation at system level of this improvement is missing. Moreover, carrying out Monte‐Carlo simulations implementing real decoding processes on significant traveled distances is time prohibitive.We propose hereafter a prediction method compatible with fast simulations to quantitatively evaluate the system performance in terms of Rate, Erroneous Second Ratio, and zapping time. This method is based on the computation of the mutual information between emitted and received symbols for QPSK modulation and turbo coding.We demonstrate that our method reaches a prediction precision of the order of 0.1 dB, which is significantly better than two classical prediction methods. Moreover, our solution reduces the simulation time by a factor of 500 compared with Monte‐Carlo. Beyond DVB‐SH application, the presented approach can be applied in a large panel of satellite mobile systems and is completely new for the satellite community. Copyright © 2012 John Wiley & Sons, Ltd.

Cooperative Error Control Mechanism Combining Cognitive Technology for Video Streaming Over Vehicular Networks

Video streaming over vehicular networks is an attractive feature to many applications, such as emergency video transmission and inter-vehicle video transmission. Vehicles accessing road-side units have a few seconds to download information and experience a high packet loss rate. Hence, this paper proposes Cooperative Error Control (CEC) mechanism combining Cognitive Technology (CT) for video streaming over wireless vehicular networks. CEC mechanism combining CT uses a cooperative error recover scheme to recover lost packets not only from a road-side unit which uses the primary channel but also from the other vehicles using a free channel. Hence, CEC mechanism with CT can enhance error recovery performance and quality of video streaming over vehicular networks. Simulation results show the error recover performance of the CEC mechanism combining CT performs better than the other related mechanisms.

The ALICE-HMPID Detector Control System: Its evolution towards an expert and adaptive system

The High Momentum Particle IDentification (HMPID) detector is a proximity focusing Ring Imaging Cherenkov (RICH) for charged hadron identification. The HMPID is based on liquid C 6F 14 as the radiator medium and on a 10 m 2 CsI coated, pad segmented photocathode of MWPCs for UV Cherenkov photon detection. To ensure full remote control, the HMPID is equipped with a detector control system (DCS) responding to industrial standards for robustness and reliability. It has been implemented using PVSS as Slow Control And Data Acquisition (SCADA) environment, Programmable Logic Controller as control devices and Finite State Machines for modular and automatic command execution. In the perspective of reducing human presence at the experiment site, this paper focuses on DCS evolution towards an expert and adaptive control system, providing, respectively, automatic error recovery and stable detector performance. HAL9000, the first prototype of the HMPID expert system, is then presented. Finally an analysis of the possible application of the adaptive features is provided.

Retransmission-Based Distributed Video Streaming with a Channel-Adaptive Packet Scheduler

This paper describes a channel-adaptive packet scheduler for improved error control performance in a peer-cooperative distributed media streaming system. The proposed packet-scheduling algorithm was designed for the case in which streaming server peers rely on an error-recovery strategy using retransmission and application-layer automatic repeat request rather than error protection using forward error correction. The proposed scheduler can maximize retransmission opportunities and reduce the frame loss rate by using the observed channel status from each server peer. Simulation results show that the proposed algorithm enhances error-recovery performance in distributed multimedia streaming better than other schedulers.

Prescription-based error concealment technique for video transmission on error-prone channels

In this article, a prescription-based error concealment (PEC) technique, based on a three-stage (diagnosis, prescription, and remedy) process, is proposed for video transmission on error-prone channels. A prescription is meant to be the best error concealment scheme among several pre-chosen ones, which are evaluated at encoder side for each MB. The collection of prescriptions for each frame is compressed and transmitted through a reliable channel to provide flexible and better error-recovery performance at decoder side. Experimental results show that the proposed PEC method is capable of achieving a PSNR improvement of up to 1.5 dB, with respect to the best single-mode scheme, when video bit rate and PER (packet error rate) are up to 512 kbps and 20%, respectively, whereas only a small amount of overheads (i.e., the coded prescriptions) is generated for reliable transmission.

Survival of the Fittest: An Active Queue Management Technique for Noisy Packet Flows

We present a novel active queue management (AQM) technique to demonstrate the efficacy of practically harnessing the predictive utility of SSR indications for improved video communication. We consider a network within which corrupted packets are relayed over multiple hops, but a certain percentage of packets needs to be dropped at an intermediate node due to congestion. We propose an AQM technique,survival of the fittest(SOTF), to be employed at the relay node, within which we use packet state information, available from SSR indications and checksums, to drop packets with the highest corruption levels. On the basis of actual 802.11b measurements we show that such a side information (SI) aware processing within the network can provide significant performance benefits over an SI-unaware scheme,random queue management(RQM), which is forced to randomly discard packets. With trace-based simulations, we show the utility of the proposed AQM technique in improving the error recovery performance of cross-layer FEC schemes. Finally, with the help of H.264-based video simulations these improvements are shown to translate into a significant improvement in video quality.

The performance of cache-based error recovery in multiprocessors

Several variations of cache-based checkpointing for rollback error recovery from transient errors in shared-memory multiprocessors have been recently developed. By modifying the cache replacement policy, these techniques use the inherent redundancy in the memory hierarchy to periodically checkpoint the computation state. Three schemes, different in the manner in which they avoid rollback propagation, are evaluated in this paper. By simulation with address traces from parallel applications running on an Encore Multimax shared-memory multiprocessor, we evaluate the performance effect of integrating the recovery schemes in the cache coherence protocol. Our results indicate that the cache-based schemes can provide checkpointing capability with low performance overhead, but with uncontrollable high variability in the checkpoint interval.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Performance measurement in token ring networks

Applications such as manufacturing or process control impose stringent requirements on communication networks with respect to the properties of timeliness and robustness. In real world networks these properties are determined first by the efficiency of the protocol realizations and second by the efficiency and scope of the recovery mechanisms. In this paper we investigate an ISO 8802/5 token ring network using measurements taken in a testbed installation using PC-AT type stations. While these no longer represent the current generation of work-stations, many conclusions remain unchanged. Concepts realized in our token ring testbed include flexible traffic generation, centralized experiment control, decentralized measurement and a high precision global clock. We include measurements characterizing the user-related delay performance. Our measurements show that at high network loads there can be a significant reduction in packet-transfer delay for priority traffic. Unique in this paper are measurements of the error-recovery performance of the network.

Recovery Times of Decision Feedback Equalizers on Noiseless Channels

The performance of decision feedback equalizers (DFE's) working on a noiseless channel with correct tap weights is studied. We show that the space of channel parameters can accordingly be partitioned into a finite number of sets. The error recovery performance of a DFE is the same for all DFE's within one such set, and is determinable. We also discuss some tight bounds for recovery time statistics, which are particularly important when the number of equalizer taps is not small. We argue that minimum phase or near minimum phase character for the channel does not necessarily guarantee short recovery time.

Error Tolerant Adaptive Algorithms for Delta-Modulation Coding

This paper investigates the adaption of qnantizer step size in voice coding circuits. Techniques which maintain the decoder step size in the presence of channel errors have been evaluated. Graphs are presented for the comparison of error recovery performance. Practical considerations favor one algorithm, and its digital implementation has been described in the paper. Laboratory measurements of step-size error recovery and SNR performance have been included to verify the theory.

Optimization of error recovery in syntax-directed Parsing algorithms

The syntactic error recovery of automatically generated recognizers is considered with two related systems for automatically generating syntactic error recovery presented, one for a Floyd production language recognizer, the other for a recursive descent recognizer. The two systems have been implemented for a small language consisting of a subset of ALGOL. When compared with each other and with a commercial ALGOL compiler, the results indicate that automatically generated syntactic error recovery can exceed the performance of reasonable hand-coded error recovery.