Intelligent Dynamic Heterogeneous Redundancy Architecture for IoT Systems

The conventional dynamic heterogeneous redundancy(DHR)architecture suffers from the security threats caused by the stability differences and similar vulnerabilities among the executors.To overcome these challenges,we propose an intelligent DHR architecture,which is more feasible by intelligently combining the random distribution based dynamic scheduling algorithm(RD-DS)and information weight and heterogeneity based arbitrament(IWHA)algorithm.In the proposed architecture,the random distribution function and information weight are employed to achieve the optimal selection of executors in the process of RD-DS,which avoids the case that some executors fail to be selected due to their stability difference in the conventional DHR architecture.Then,through introducing the heterogeneity to restrict the information weights in the procedure of the IWHA,the proposed architecture solves the common mode escape issue caused by the existence of multiple identical error output results of similar vulnerabilities.The experimental results characterize that the proposed architecture outperforms in heterogeneity,scheduling times,security,and stability over the conventional DHR architecture under the same conditions.

Multi-Label Feature Selection Based on Improved Ant Colony Optimization Algorithm with Dynamic Redundancy and Label Dependence

The world produces vast quantities of high-dimensional multi-semantic data.However,extracting valuable information from such a large amount of high-dimensional and multi-label data is undoubtedly arduous and challenging.Feature selection aims to mitigate the adverse impacts of high dimensionality in multi-label data by eliminating redundant and irrelevant features.The ant colony optimization algorithm has demonstrated encouraging outcomes in multi-label feature selection,because of its simplicity,efficiency,and similarity to reinforcement learning.Nevertheless,existing methods do not consider crucial correlation information,such as dynamic redundancy and label correlation.To tackle these concerns,the paper proposes a multi-label feature selection technique based on ant colony optimization algorithm(MFACO),focusing on dynamic redundancy and label correlation.Initially,the dynamic redundancy is assessed between the selected feature subset and potential features.Meanwhile,the ant colony optimization algorithm extracts label correlation from the label set,which is then combined into the heuristic factor as label weights.Experimental results demonstrate that our proposed strategies can effectively enhance the optimal search ability of ant colony,outperforming the other algorithms involved in the paper.

Analysis of wheel-rail adhesion redundancy considering the thirdbody medium on the rail surface

Purpose–In response to the problem of insufficient traction/braking adhesion force caused by the existence of the third-body medium on the rail surface,this study aims to analyze the utilization of wheel-rail adhesion coefficient under different medium conditions and propose relevant measures for reasonable and optimized utilization of adhesion to ensure the traction/braking performance and operation safety of trains.Design/methodology/approach–Based on the PLS-160 wheel-rail adhesion simulation test rig,the study investigates the variation patterns of maximum utilized adhesion characteristics on the rail surface under different conditions of small creepage and large slip.Through statistical analysis of multiple sets of experimental data,the statistical distribution patterns of maximum utilized adhesion on the rail surface are obtained,and a method for analyzing wheel-rail adhesion redundancy based on normal distribution is proposed.The study analyzes the utilization of traction/braking adhesion,as well as adhesion redundancy,for different medium under small creepage and large slip conditions.Based on these findings,relevant measures for the reasonable and optimized utilization of adhesion are derived.Findings–When the third-body medium exists on the rail surface,the train should adopt the low-level service braking to avoid the braking skidding by extending the braking distance.Compared with the current adhesion control strategy of small creepage,adopting appropriate strategies to control the train’s adhesion coefficient near the second peak point of the adhesion coefficient-slip ratio curve in large slip can effectively improve the traction/braking adhesion redundancy and the upper limit of adhesion utilization,thereby ensuring the traction/braking performance and operation safety of the train.Originality/value–Most existing studies focus on the wheel-rail adhesion coefficient values and variation patterns under different medium conditions,without considering whether the rail surface with different medium can provide sufficient traction/braking utilized adhesion coefficient for the train.Therefore,there is a risk of traction overspeeding/braking skidding.This study analyzes whether the rail surface with different medium can provide sufficient traction/braking utilized adhesion coefficient for the train and whether there is redundancy.Based on these findings,relevant measures for the reasonable and optimized utilization of adhesion are derived to further ensure operation safety of the train.

Novel Double Modular Redundancy Based Fault-Tolerant FIR Filter for Image Denoising

In signal processing and communication systems,digital filters are widely employed.In some circumstances,the reliability of those systems is crucial,necessitating the use of fault tolerant filter implementations.Many strategies have been presented throughout the years to achieve fault tolerance by utilising the structure and properties of the filters.As technology advances,more complicated systems with several filters become possible.Some of the filters in those complicated systems frequently function in parallel,for example,by applying the same filter to various input signals.Recently,a simple strategy for achieving fault tolerance that takes advantage of the availability of parallel filters was given.Many fault-tolerant ways that take advantage of the filter’s structure and properties have been proposed throughout the years.The primary idea is to use structured authentication scan chains to study the internal states of finite impulse response(FIR)components in order to detect and recover the exact state of faulty modules through the state of non-faulty modules.Finally,a simple solution of Double modular redundancy(DMR)based fault tolerance was developed that takes advantage of the availability of parallel filters for image denoising.This approach is expanded in this short to display how parallel filters can be protected using error correction codes(ECCs)in which each filter is comparable to a bit in a standard ECC.“Advanced error recovery for parallel systems,”the suggested technique,can find and eliminate hidden defects in FIR modules,and also restore the system from multiple failures impacting two FIR modules.From the implementation,Xilinx ISE 14.7 was found to have given significant error reduction capability in the fault calculations and reduction in the area which reduces the cost of implementation.Faults were introduced in all the outputs of the functional filters and found that the fault in every output is corrected.

Microcontroller Design Based on Dynamic Heterogeneous Redundancy Architecture

Redundancy control can effectively enhance the stability and robustness of a system.Based on the conventional redundancy control switchover and majority arbitration strategy,this paper introduces the concept of heterogeneity and dynamics,constructs a dynamic heterogeneous redundancy-based microcontroller architecture DHR-MCU,and designs a fixed-leader distributed consensus algorithm that satisfies the program running state control of this architecture.The theoretical analysis and actual measurement of the prototype system prove that this architecture has good anti-attack and self-recovery capabilities under normal functions and performances and meets the general robust features in terms of safety and security.

Multi-Objective Redundancy Optimization of Continuous-Point Robot Milling Path in Shipbuilding

The 6-DOF manipulator provides a new option for traditional shipbuilding for its advantages of vast working space,low power consumption,and excellent flexibility.However,the rotation of the end effector along the tool axis is functionally redundant when using a robotic arm for five-axis machining.In the process of ship construction,the performance of the parts’protective coating needs to bemachined tomeet the Performance Standard of Protective Coatings(PSPC).The arbitrary redundancy configuration in path planning will result in drastic fluctuations in the robot joint angle,greatly reducing machining quality and efficiency.There have been some studies on singleobjective optimization of redundant variables,However,the quality and efficiency of milling are not affected by a single factor,it is usually influenced by several factors,such as the manipulator stiffness,the joint motion smoothness,and the energy consumption.To solve this problem,this paper proposed a new path optimization method for the industrial robot when it is used for five-axis machining.The path smoothness performance index and the energy consumption index are established based on the joint acceleration and the joint velocity,respectively.The path planning issue is formulated as a constrained multi-objective optimization problem by taking into account the constraints of joint limits and singularity avoidance.Then,the path is split into multiple segments for optimization to avoid the slow convergence rate caused by the high dimension.An algorithm combining the non-dominated sorting genetic algorithm(NSGA-II)and the differential evolution(DE)algorithm is employed to solve the above optimization problem.The simulations validate the effectiveness of the algorithm,showing the improvement of smoothness and the reduction of energy consumption.

REDUNDANCY TECHNOLOGY FOR AIRCRAFT MULTI-CHANNEL DC POWER SUPPLY SYSTEM

The redundancy technology for the aircraft multi-channel DC electrical power supply system is studied. In this system, the key loads can obtain power from seven sources. The direct current bus power control unit （DC BPCU） is put forward to manage the power supply system automatically. The redundancy innovation is also applied in both hardware and software of DC BPCU. Furthermore, redundancy fault diagnosis is discussed through the existing parts. Experiments and applications show that the proposed aircraft DC power supply system possesses many advantages of high reliability, high automation and so on.

关于不使用Hash和Redundancy函数签密方案的分析与改进

在实际应用中,前向安全性和公开验证性对密码系统来说是非常重要的。分析了不使用Hash和Redundancy函数的签密方案的前向安全性和公开验证性,分析表明该方案不具备前向安全性和公开验证性。分别就其前向安全性和公开验证性提出了相应的改进方案,并对方案进行了理论上的证明。改进方案克服了原方案中不具备前向安全性或公开验证性的缺陷;而且从效率上来分析,并没有明显增加计算量或传输量。

Probabilistic Indicators of Structural Redundancy in Mechanics

The paper in the introductory part reviews various definitions and interpretations of structural redundancy in mechanics. The study focuses on the general structural redundancy of systems after sequences of component failures followed by possible load redistributions. The second section briefly summarizes the Event Oriented System Analysis and structural redundancy in terms of the conditional probabilistic entropy. Mechanical responses to adverse loads in this approach are represented by random operational and failure events in the lifetime. The general redundancy measure in the third section of the paper employs the information entropy and goes beyond existing formulations since it includes all functional modes in service. The paper continues with a summary of traditional redundancy indices. In addition, it proposes an alternative redundancy index that accounts for the transition to secondary functional level in case of failures of primary components. The example of a ship structure illustrates the usage of the conditional entropy of subsystems of operational events and compares it to the traditional and newly proposed redundancy indices. The study at the end investigates how to enhance the safety of structures by using the redundancy based design.

Joint Source-Channel Decoding of EVRC Speech Encoder Using Residual Redundancy

The enhanced variable rate codec (EVRC) is a standard for the 'Speech ServiceOption 3 for Wideband Spread Spectrum Digital System,' which has been employed in both IS-95cellular systems and ANSI J-STC-008 PCS (personal communications systems). This paper concentrateson channel decoders that exploit the residual redundancy inherent in the enhanced variable ratecodec bitstream. This residual redundancy is quantified by modeling the parameters as first orderMarkov chains and computing the entropy rate based on the relative frequencies of transitions.Moreover, this residual redundancy can be exploited by an appropriately 'tuned' channel decoder toprovide substantial coding gain when compared with the decoders that do not exploit it. Channelcoding schemes include convolutional codes, and iteratively decoded parallel concatenatedconvolutional 'turbo' codes.

New approach to eliminate structural redundancy in case resource pools using α mutual information

Structural redundancy elimination in case resource pools （CRP） is critical for avoiding performance bottlenecks and maintaining robust decision capabilities in cloud computing services. For these purposes, this paper proposes a novel approach to ensure redundancy elimination of a reasoning system in CRP. By using α entropy and mutual information, functional measures to eliminate redundancy of a system are developed with respect to a set of outputs. These measures help to distinguish both the optimal feature and the relations among the nodes in reasoning networks from the redundant ones with the elimination criterion. Based on the optimal feature and its harmonic weight, a model for knowledge reasoning in CRP （CRPKR） is built to complete the task of query matching, and the missing values are estimated with Bayesian networks. Moreover, the robustness of decisions is verified through parameter analyses. This approach is validated by the simulation with benchmark data sets using cloud SQL. Compared with several state-of-the-art techniques, the results show that the proposed approach has a good performance and boosts the robustness of decisions.

Comparative Study on Structural Redundancy of Cable-Stayed and Extradosed Bridges Through Safety Assessment of Their Stay Cables

This study provides new insights into the comparison of cable-stayed and extradosed bridges based on the safety assessment of their stay cables.These bridges are often regarded as identical structures owing to the use of inclined cables;however,the international standards for bridge design stipulate different safety factors for stay cables of both types of bridges.To address this misconception,a comparative study was carried out on the safety factors of stay cables under fatigue and ultimate limit states by considering the effects of various untoward and damaging factors,such as overloading,cable loss,and corrosion.The primary goal of this study is to describe the structural disparities between both types of bridges and evaluate their structural redundancies by employing deterministic and nondeterministic methods.To achieve this goal,three-dimensional finite-element models of both bridges were developed based on the current design guidelines for stay cables in Japan.After the balanced states of the bridge models were achieved,static analyses were performed for different safety factors of stay cables in a parametric manner.Finally,the first-order reliability method and Monte Carlo method were applied to determine the reliability index of stay cables.The analysis results show that cable-stayed and extradosed bridges exhibit different structural redundancies for different safety factors under the same loading conditions.Moreover,a significant increase in structural redundancy occurs with an incremental increase in the safety factors of stay cables.

Genetic Algorithm-Based Redundancy Optimization Method for Smart Grid Communication Network

This paper proposes a redundancy optimization method for smart grid Advanced Metering Infrastructure(AMI) to realize economy and reliability targets.AMI is a crucial part of the smart grid to measure,collect,and analyze data about energy usage and power quality from customer premises.From the communication perspective,the AMI consists of smart meters,Home Area Network(HAN) gateways and data concentrators;in particular,the redundancy optimization problem focus on deciding which data concentrator needs redundancy.In order to solve the problem,we first develop a quantitative analysis model for the network economic loss caused by the data concentrator failures.Then,we establish a complete redundancy optimization model,which comprehensively consider the factors of reliability and economy.Finally,an advanced redundancy deployment method based on genetic algorithm(GA) is developed to solve the proposed problem.The simulation results testify that the proposed redundancy optimization method is capable to build a reliable and economic smart grid communication network.

Redundancy Elimination in GPRS network

The mechanisms of TCP’s retransmission and reset will result in redundant packets. These redundant packets are often sent unnecessarily to the user over a slow last-hop link delaying useful traffic. This is a problem for wide-area wireless links, such as General Packet Radio Service (GPRS), because unnecessary transmissions waste already limited radio bandwidth, battery power at the mobile terminal and incurs monetary cost due to charging by data volume. The paper first describes a GPRS model, then discusses how to eliminate the redundant packets in GPRS network and presents the simulation results in Network Simulation 2 (NS 2). The more traffic is, the more the network can benefit. In heavy traffic, it can even get more than 30% improvement in throughput. Average delay and loss percent are also lowered.

Synthesis of Branched Chains with Actuation Redundancy for Eliminating Interior Singularities of 3T1R Parallel Mechanisms

Although it is common to eliminate the singularity of parallel mechanism by adding the branched chain with actuation redundancy, there is no theory and method for the configuration synthesis of the branched chain with actuation redundancy in parallel mechanism. Branched chains with actuation redundancy are synthesized for eliminating interior singularity of 3-translational and 1-rotational（3T1R） parallel mechanisms. Guided by the discriminance method of hybrid screw group according to Grassmann line geometry, all the possibilities are listed for the occurrence of interior singularities in 3T1R parallel mechanism. Based on the linear relevance of screw system and the principles of eliminating parallel mechanism singularity with actuation redundancy, different types of branched chains with actuation redundancy are synthesized systematically to indicate the layout and the number of the branched chainsinterior with actuation redundancy. A general method is proposed for the configuration synthesis of the branched chains with actuation redundancy of the redundant parallel mechanism, and it builds a solid foundation for the subsequent performance optimization of the redundant actuation parallel mechanism.

Broadcasting with Controlled Redundancy and Improved Localization in Wireless Sensor Networks

Wireless sensor networks （WSNs） consist of sensor nodes that broadcast a message within a network. Efficient broadcasting is a key requirement in sensor networks and has been a focal point of research over the last few years. There are many challenging tasks in the network, including redundancy control and sensor node localization that mainly depend on broadcasting. In this paper, we propose a broadcasting algorithm to control redundancy and improve localization （BACRIL） in WSNs. The proposed algorithm incorporates the benefits of the gossip protocol for optimizing message broadcasting within the network. Simulation results show a controlled level of redundancy, which is up to 57.6% if the number of sensor nodes deployed in a 500 m×500 m area are increased from 50 to 500.

Feature Selection via Analysis of Relevance and Redundancy

Feature selection is an important problem in pattern classification systems. High dimension fisher criterion（HDF） is a good indicator of class separability. However, calculating the high dimension fisher ratio is difficult. A new feature selection method, called fisher-and-correlation （FC）, is proposed. The proposed method is combining fisher criterion and correlation criterion based on the analysis of feature relevance and redundancy. The proposed methodology is tested in five different classification applications. The presented resuits confirm that FC performs as well as HDF does at much lower computational complexity.

Simulation method for reliability of TT&C mission with high redundancy and small time horizon

The tracking, telemetry and command （TT＆C） mission is extremely reliable for its characters of small time horizon and high redundancy. The combined forcing and failure biasing （CFFB） method that is usually used for simulating the unreliability of the highly dependable mission system seems not so efficient for the TT＆C mission. The concept about the importance of failure transition is proposed based on the logical relationship between TT＆C mission and its involved resources. Then, the importance is used for readjusting the transition rate of the failure transition when using the forcing and failure biasing during the simulation. Examples show that the improved CFFB method can evidently increase the occurrence of the TT＆C mission failure event and decrease the sample variance. More redundancy of the TT＆C mission leads to the improved CFFB method more efficient.

Smart Material Based Complex Mode Active Control of Flexible Manipulators with Kinematic Redundancy

An active control methodology is presented for suppressing the vibratoryresponse of flexible redundant manipulators with bonded piezoceramic actuators and strain gagesensors. Firstly, the dynamic equation of the manipulator is decoupled by means of the complex modetheory and the state-space expression of the controlled system is developed. Secondly, a continuouslinear quadratic regulator (LQR) state feedback controller is designed based on the minimumprinciple. Thirdly, a full-order Luenberger state observer featuring an assigned degree of stabilityis determined via the duality between control and estimation. Finally, a numerical simulation iscarried out on a planar 3R flexible redundant manipulator. The simulation results reveal that thedynamic performance of the system is improved rapidly and significantly.

PARAMETRIC IDENTIFICATION OF PARALLEL MANIPULATOR WITH REDUNDANCY DRIVEN BY PNEUMATIC MUSCLES

A new parameter estimation algorithm is proposed for parametric identification of a parallel manipulator driven by pneumatic muscles with redundancy. Due to the special physical properties of the parallel manipulator studied, the regression model for parametric identification is characterized by multieollinearity, which will result in unreliable and inaccurate parameter estimations with large eovarianee if the conventional parameter estimation algorithm based on single error minimizing criterion is used. To improve the quality of parameter estimation and achieve high precise posture trajectory tracking control of the parallel manipulator, a new parameter estimation algorithm based on composite error minimizing criterion is developed in need of theoretical contractive forces of pneumatic muscles. The experimental results indicate that the proposed algorithm integrated with adaptive robust control could provide reliable parametric identification and greatly enhance the control accuracy in the trajectory tracking control of the parallel manipulator, and that the variation of known theoretical contractive forces of pneumatic muscles has slight influence on the control performance.