Redundant Version Research Articles

Adaptive Seamless Redundancy to Achieve Highly Dependable MQTT Communication

Nowadays, large enterprises, critical infrastructures, and utilities are complex systems, and consist of a number of sub-systems, often located far away from each other, that coordinate their operations over geographic networks. Typically, they are interconnected through the Internet and communicate by means of TCP/IP-based protocols. When system-level resilience is required, extremely high dependability is demanded from the network. In this paper a solution is described and evaluated that loosely resembles SDN architectures. A redundant version of MQTT is used for the data plane, whereas an adaptive mechanism is implemented in the control plane that evaluates the quality of paths and dynamically selects the best choice. To maximize dependability, yet keeping resource consumption to acceptable levels, concepts borrowed from Reinforcement Learning are exploited. An experimental campaign corroborated our expectations and showed the practical feasibility of our proposal.

HARQ-Based Grant-Free NOMA for mMTC Uplink

Massive machine-type communication (mMTC) is one of the most rewarding and at the same time challenging components in the fifth-generation (5G) cellular solutions supporting the Internet of Things (IoT). The 5G mMTC is considering the use of a combination of two key mMTC enabling technologies-grant-free (GF) transmission and nonorthogonal multiple-access (NOMA), called GF-NOMA, which can potentially exploit the advantages of both schemes. A primary challenge in GF-NOMA is to reduce the packet drop rate. Owing to the decentralized nature of the GF schemes and the lack of control over user equipment, only hybrid automatic repeat request (HARQ) Type I has been employed for enhancing the reliability of GF-NOMA so far. In this article, uplink GF-NOMA transmission schemes using HARQ Type III are proposed. Two types of packet combining-1) chase combining and 2) incremental redundancy combining are considered. Moreover, we introduce a GF single-transmission (GFST) scheme where all redundancy versions of the packet are transmitted in one shot. We present a comprehensive evaluation of both the GF and the conventional grant-based methods in mMTC scenarios and demonstrate the superiority of our proposed methods over the existing ones.

Algorithm source codes generation for ensuring N-version software diversity

Diversity is one of the fundamental principles for N-version software development. The development of redundant versions can significantly improve the reliability of software, but it is more time and labour consuming. Business and manufacturing require a higher level of software reliability. The task of reducing the lead-time and cost effectiveness becomes more important when developing N-version software for such industries. It is proposed to use automatic source code generation to create N-version software. The use of domain-specific language for the intermediate representation of the algorithm simplifies code generation in the target programming language. The authors discuss a new conceptual model of two-step code translation for N-version software. The proposed approach will simplify the process of N-version software development and reduce the number of required resources. The paper contains an example of C code generation as a target programming language, using flowcharts as a graphical representation of the source algorithm. The described approach is intended for use in safety-critical industries.

Design and evaluation of a new structure for fault-tolerance full-adder based on quantum-dot cellular automata

Quantum-dot Cellular Automata (QCA) has emerged as an attractive alternative to Complementary Metal Oxide Semiconductor (CMOS) technology in the nanoscale era. In designing arithmetic circuits, an efficient adder can play a significant role. The next generation of digital systems will be used QCA as desired technology. The QCA computational and arithmetic systems will be facilitated using an efficient QCA-based full-adder. The defects of manufacturing and variations still remain as a problem in QCA-based circuits. Being unreliable and error-prone are the weaknesses of these circuits. Therefore, in this paper, a novel QCA-based fault-tolerant full-adder design using cells redundancy is suggested. Three elements such as misalignment, missing and dislocation cells are important in analyzing the fault properties. Further, this paper aims to study the functionality and the fault-tolerant property of the proposed full-adder in the presence of QCA deposition faults. The obtained results using QCADesigner have demonstrated the proposed full-adder has better performance in terms of latency, complexity, and area in comparison to the previous full-adder designs. Also, the redundant version of full-adder has simple and strong structure compared to standard styles.

Abstract P441: Accelerated Age-dependent Cardiovascular and Cognitive Decline in Dahl-S Rats is Associated with Elevated Levels of an Endogenous Na/K-ATPase Inhibitor

Age-associated central arterial stiffening contributes to both cerebral arterial fibrosis and to cognitive impairment. Accelerated aging, accompanied by a gradual increase in blood pressure (BP) and aortic remodeling, occurs in Dahl-S rats (DSS) vs. normotensive Sprague-Dawley rats (S-D) counterparts even in the absence of a high salt intake. A novel pro-hypertensive factor marinobufagenin (MBG) is implicated in DSS hypertension. Here we determined whether an increase in MBG is also implicated in age-associated arterial remodeling in DSS. Methods: Life span was measured in 60 S-D and 78 DSS. BP, pulse wave velocity (PWV), behavioral water maze test, ANGII, MBG and aortic collagen were assessed in 3 and 9-mo S-D and DSS on a normal 0.5% NaCl intake. Results: Median life span in DSS is reduced by 50% vs. S-D (12±1 vs. 24±2 mo, p<0.01). At 3-mo DSS had higher SBP, PWV, ANGII, MBG, aortic and large cerebral arterial wall remodeling vs. 3-mo S-D (Table). Between 3 and 9-mo DSS, but not S-D, exhibited further increase in SBP, PWV, MBG and aortic collagen deposition. In a redundant place-cue version of the water maze test, 3-mo DSS demonstrated numerically impaired spatial hippocampal memory vs. 3-mo S-D, and by 9-mo, performance in DSS suggested the development of motor impairments, thus precluding an uncontaminated assessment of their spatial memory. Conclusions: In DSS high MBG occurred concurrently with fibrosis of aorta and large cerebral arteries and numerically impaired spatial memory. With advancing age of DSS further increase in BP, aortic stiffness and spatial learning/motor deficit occurred in context with an increase in MBG, which suggested an implication of MBG in these declines.

RSAT matrix-clustering: dynamic exploration and redundancy reduction of transcription factor binding motif collections.

Transcription factor (TF) databases contain multitudes of binding motifs (TFBMs) from various sources, from which non-redundant collections are derived by manual curation. The advent of high-throughput methods stimulated the production of novel collections with increasing numbers of motifs. Meta-databases, built by merging these collections, contain redundant versions, because available tools are not suited to automatically identify and explore biologically relevant clusters among thousands of motifs. Motif discovery from genome-scale data sets (e.g. ChIP-seq) also produces redundant motifs, hampering the interpretation of results. We present matrix-clustering, a versatile tool that clusters similar TFBMs into multiple trees, and automatically creates non-redundant TFBM collections. A feature unique to matrix-clustering is its dynamic visualisation of aligned TFBMs, and its capability to simultaneously treat multiple collections from various sources. We demonstrate that matrix-clustering considerably simplifies the interpretation of combined results from multiple motif discovery tools, and highlights biologically relevant variations of similar motifs. We also ran a large-scale application to cluster ∼11 000 motifs from 24 entire databases, showing that matrix-clustering correctly groups motifs belonging to the same TF families, and drastically reduced motif redundancy. matrix-clustering is integrated within the RSAT suite (http://rsat.eu/), accessible through a user-friendly web interface or command-line for its integration in pipelines.

Design and characterization of a new fault-tolerant full-adder for quantum-dot cellular automata

A novel fault-tolerant full-adder for quantum-dot cellular automata is presented. Quantum-dot cellular automata (QCA) is an emerging technology and a possible alternative for semiconductor transistor based technologies. A novel fault-tolerant full-adder is proposed in this paper: This component is suitable for designing fault-tolerant QCA circuits. The redundant version of full-adder is simple in structure and more robust than the standard style for this device. By considering two-dimensional arrays of QCA cells, fault properties of such block full-adder can be analyzed in terms of misalignment, missing and dislocation cells. In order to verify the functionality of the proposed device, some physical proofs are provided. The results confirm our claims and its usefulness in designing digital circuits.

Image denoising with 2D scale-mixing complex wavelet transforms.

This paper introduces an image denoising procedure based on a 2D scale-mixing complex-valued wavelet transform. Both the minimal (unitary) and redundant (maximum overlap) versions of the transform are used. The covariance structure of white noise in wavelet domain is established. Estimation is performed via empirical Bayesian techniques, including versions that preserve the phase of the complex-valued wavelet coefficients and those that do not. The new procedure exhibits excellent quantitative and visual performance, which is demonstrated by simulation on standard test images.

Hybrid time and hardware redundancy to mitigate SEU effects on SRAM-FPGAs: Case study over the MicroLAN protocol

SRAM-based field programmable gate arrays (FPGAs) are particularly sensitive to single event upsets caused by high-energy space radiation. Single Event Upset (In order to successfully deploy the SRAM-FPGA based designs in aerospace applications, designers need to adopt suitable hardening techniques. In this paper, we describe novel hybrid time and hardware redundancy (HT&HR) structures to mitigate SEU effects on FPGA, especially digital circuits that are designed with bidirectional ports. The proposed structures that combine time and hardware redundancy decrease the SEU propagation mechanisms among the redundant hard units. Analysis results and fault injection experiments on some standard ISCAS benchmarks and MicroLAN protocol, as a case study over the bidirectional ports, show that the capability of tolerating SEU effects in HT&HR technique increases up to 70 times with respect to solely hardware redundant versions. On average, the proposed method provides 39.2 times improvement against single upset faults and 14.9 times for double upset faults; however it imposes about 14.7% area overhead. Also, for the considered benchmarks, HT&HR circuits become 8.8% faster on the average than their TMR versions.

Texture Modeling Using Contourlets and Finite Mixtures of Generalized Gaussian Distributions and Applications

In this paper, we develop a new framework for contourlet-based statistical modeling using finite Mixtures of Generalized Gaussian distributions ( MoGG). On the one hand, given the rich directional information provided by the contourlet transform (CT), we propose to use a redundant version of the CT, which describes texture structures more accurately. On the other hand, we use MoGG modeling of contourlet coefficients distribution, which allows for precise capturing of a wide range of histogram shapes and provides better description and discrimination of texture than single probability density functions (pdfs). Moreover, we propose three applications for the proposed approach, namely: (1) texture retrieval, (2) fabric texture defect detection, and 3) infrared (IR) face recognition. We compare two implementations of the CT: standard CT ( SCT) and redundant CT ( RCT). We show that the proposed approach yields better results in the applications studied compared to recent state-of-the-art methods.

A new quantum-dot cellular automata fault-tolerant five-input majority gate

A new fault-tolerant five-input majority gate for quantum-dot cellular automata (QCA) is presented. There has been considerable research on QCA as an emerging computing scheme in the nanoscale regimes. Two main logic elements for implementation with QCA are “Majority gate” and “Inverter”. In this paper, we propose a new approach to the design of fault-tolerant five-input majority gate by considering two-dimensional arrays of QCA cells. We analyze fault-tolerance properties of such block five-input majority gate with respect to misalignment, missing, and dislocation cells. In order to verify the functionality of the proposed component some physical proofs are provided. Our results clearly demonstrate the redundant version of the block five-input majority gate is more robust than the standard style for this gate and its usefulness in designing arithmetic circuits.

Improving Cyber Resiliency of Cloud Application Services by Applying Software Behavior Encryption (SBE)

The objective of this work is to define and measure cyber resiliency of the “cloud” in a Moving Target Defense (MTD) environment that applies the Software Behavior Encryption (SBE) method. Implementation of SBE has shown to increase vulnerability tolerance in a particular software system by introducing software diversity and redundant version shuffling to obfuscate the system to attackers. With this in mind, this paper nominates attack surface, confidentiality, integrity, availability, and survivability as the critical components of cyber resiliency, and a notional example is provided to demonstrate the components application and aggregation.

New efficient five-input majority gate for quantum-dot cellular automata

A novel fault-tolerant five-input majority gate for quantum-dot cellular automata is presented. Quantum-dot cellular automata (QCA) is an emerging technology which is considered to be presented in future computers. Two principle logic elements in QCA are “majority gate” and “inverter.” In this paper, we propose a new approach to the design of fault-tolerant five-input majority gate by considering two-dimensional arrays of QCA cells. We analyze fault tolerance properties of such block five-input majority gate in terms of misalignment, missing, and dislocation cells. Some physical proofs are used for verifying five-input majority gate circuit layout and functionality. Our results clearly demonstrate that the redundant version of the block five-input majority gate is more robust than the standard style for this gate.

Novel Design for Quantum Dots Cellular Automata to Obtain Fault-Tolerant Majority Gate

Quantum-dot Cellular Automata (QCA) is one of the most attractive technologies for computing at nanoscale. The principle element in QCA is majority gate. In this paper, fault-tolerance properties of the majority gate is analyzed. This component is suitable for designing fault-tolerant QCA circuits. We analyze fault-tolerance properties of three-input majority gate in terms of misalignment, missing, and dislocation cells. In order to verify the functionality of the proposed component some physical proofs using kink energy (the difference in electrostatic energy between the two polarization states) and computer simulations using QCA Designer tool are provided. Our results clearly demonstrate that the redundant version of the majority gate is more robust than the standard style for this gate.

Error-resilient video coding with end-to-end rate-distortion optimized at macroblock level

Abstract Intra macroblock refreshment is an effective approach for error-resilient video coding. In this paper, in addition to intra coding, we propose to add two macroblock coding modes to enhance the transmission robustness of the coded bitstream, which are inter coding with redundant macroblock and intra coding with redundant macroblock. The selection of coding modes and the parameters for coding the redundant version of the macroblock are determined by the rate-distortion optimization. It is worth mentioning that the end-to-end distortion is employed in the optimization procedure, which considers the channel conditions. Extensive simulation results show that the proposed approach outperforms other error-resilient approaches significantly; for some video sequences, the average PSNR can be up to 4 dB higher than that of the Optimal Intra Refreshment approach.

A New Multiple Versions Incremental Creation Algorithm

The multi-versioning technique based on object replication strategy can meet consistency model while the conflict operations occur in the cooperative graphics editing systems(CGES),but it does not efficiently solve conflict between non-geometry attribute operations and complex graphics objects. A new distributed multi-versioning model based on version replication is proposed for consistency maintenance of discordant conflicting operations according to the conflicting features and types of concurrent operations in CGES. To guarantee intention of conflicting operations, leaf-versions must be replicated from the original version based on the reduce strategy, and then applying conflicting operations to the corresponding object of the different replicated versions. The leaf-versions can be created by MOVIC algorithm in which the comparison-number of compatible operations is too much. A Fast Multiple Versions Incremental Creation (FMVIC) algorithm based on the compatible and conflict group is presented in this paper. The final versions constructed by the FMVIC algorithm is the same as that constructed by the MOVIC algorithm, but it can decrease the comparison-number of compatible operations and narrow the scope of comparison operations for the removing redundant versions.

The Pairing of a Wavelet Basis With a Mildly Redundant Analysis via Subband Regression

A distinction is usually made between wavelet bases and wavelet frames. The former are associated with a one-to-one representation of signals, which is somewhat constrained but most efficient computationally. The latter are over-complete, but they offer advantages in terms of flexibility (shape of the basis functions) and shift-invariance. In this paper, we propose a framework for improved wavelet analysis based on an appropriate pairing of a wavelet basis with a mildly redundant version of itself (frame). The processing is accomplished in four steps: 1) redundant wavelet analysis, 2) wavelet-domain processing, 3) projection of the results onto the wavelet basis, and 4) reconstruction of the signal from its nonredundant wavelet expansion. The wavelet analysis is pyramid-like and is obtained by simple modification of Mallat's filterbank algorithm (e.g., suppression of the down-sampling in the wavelet channels only). The key component of the method is the subband regression filter (Step 3) which computes a wavelet expansion that is maximally consistent in the least squares sense with the redundant wavelet analysis. We demonstrate that this approach significantly improves the performance of soft-threshold wavelet denoising with a moderate increase in computational cost. We also show that the analysis filters in the proposed framework can be adjusted for improved feature detection; in particular, a new quincunx Mexican-hat-like wavelet transform that is fully reversible and essentially behaves the (gamma/2)th Laplacian of a Gaussian.

Complex Wavelet Bases, Steerability, and the Marr-Like Pyramid

Our aim in this paper is to tighten the link between wavelets, some classical image-processing operators, and David Marr's theory of early vision. The cornerstone of our approach is a new complex wavelet basis that behaves like a smoothed version of the Gradient-Laplace operator. Starting from first principles, we show that a single-generator wavelet can be defined analytically and that it yields a semi-orthogonal complex basis of L2 (R2), irrespective of the dilation matrix used. We also provide an efficient FFT-based filterbank implementation. We then propose a slightly redundant version of the transform that is nearly translation-invariant and that is optimized for better steerability (Gaussian-like smoothing kernel).We call it the Marr-like wavelet pyramid because it essentially replicates the processing steps in Marr's theory of early vision.We use it to derive a primal wavelet sketch which is a compact description of the image by a multiscale, subsampled edge map. Finally, we provide an efficient iterative algorithm for the reconstruction of an image from its primal wavelet sketch.

PET Image Denoising Using a Synergistic Multiresolution Analysis of Structural (MRI/CT) and Functional Datasets

PET allows the imaging of functional properties of the living tissue, whereas other modalities (CT, MRI) provide structural information at significantly higher resolution and better image quality. Constraints for injected radioactivity, technologic limitations of current instrumentation, and inherent spatial uncertainties on the decaying process affect the quality of PET images. In this article we illustrate how structural information of matched anatomic images can be used in a multiresolution model to enhance the signal-to-noise ratio of PET images. The model states a flexible relation between function and structure in the brain and replaces high-resolution information of PET images with appropriately scaled MRI or CT local detail. The method can be naturally extended to other functional imaging modalities (SPECT, functional MRI). The methodology is based on the multiresolution property of the wavelet transform (WT). First, the coregistered structural image (MRI/CT) is downgraded to the resolution of the PET volume through appropriate filtering. Second, a redundant version of the WT is applied to both volumes. Third, a linear model is applied to the set of local coefficients of both image volumes and resulting parameters are recorded. The overall set of linear coefficients is then modeled as a mixture of multivariate gaussian distributions and fitted through a k-means algorithm. Finally, the local wavelet coefficients of the PET image are substituted by the corresponding values of the MRI/CT set calibrated according to the resulting clustering. The methodology was validated on digital simulated images and clinical data to evaluate its quantitative potential for individual as well as group analysis. Application to real and simulated datasets shows very effective noise reduction (15% SD) while resolution is preserved. The methodology is robust to errors in the coregistration parameters, practical to implement, and computationally fast.

Fact sheet of the MÉTA database 1.2

The survey results of the MÉTA program are managed with centralised relational database management system (MS SQL 2000) developed and set up in a local area network. Besides the MÉTA database server, a publishing server, an archiving server and a GIS workstation were applied. The core information entities of the MÉTA database are: information subproject, MÉTA quadrate, MÉTA hexagon, (semi-)natural habitat, potential vegetation with numerous habitats, landscape ecology and land use attributes, and surveyor. This information is coded in the nine main tables of the normalised database. In the recent state there are almost 1,500,000 records in the main tables that are managed in 241 independent fields. The published version of the MÉTA database supports the query service, and handles this information in 7 denormalised main tables. This much more redundant version is 11 GB in size. The 20.6% (179 man-month) of the human resources in the MÉTA program were devoted to the information tasks (set up and preparation, MÉTA database and information system development, replenishment and quality assessment, MÉTA query, GIS and printing services) between 2002 and 2007. The basic structure of the MÉTA database version 1.2 is finalised and the main functions regarding data processing have been developed. The accomplishment is higher than 90%, quality assessment is under way, while scientific verification and data harmonisation are started. The area of (semi-)natural and degraded vegetation of Hungary is estimated to 1,800,000 hectares (19.4% of the country) of which the natural, semi-natural is about 1,200,000 hectares (12.9% of the country). All of these are highly fragmented and unevenly distributed over the country. It is shown by several basic figures, professional content and quality measure facts of the database. There is also a fact sheet of surveyors that shapes the important characters of their field experience profile, too.