Dynamic Redundancy Research Articles

Dynamic redundancy as a mechanism to optimize collective random searches.

We explore the case of a group of random walkers looking for a target randomly located in space, such that the number of walkers is not constant but new ones can join the search, or those that are active can abandon it, with constant rates r_{b} and r_{d}, respectively. Exact analytical solutions are provided both for the fastest-first-passage time and for the collective time cost required to reach the target, for the exemplifying case of Brownian walkers with r_{d}=0. We prove that even for such a simple situation there exists an optimal rate r_{b} at which walkers should join the search to minimize the collective search costs. We discuss how these results open a new line to understand the optimal regulation in searches conducted through multiparticle random walks, e.g., in chemical or biological processes.

Study on the mechanism and countermeasures of progressive collapse in deep excavation retained by multilayer struts

There is still a lack of research on the resilient design of excavations retained by multilayer struts against progressive collapse. This paper utilizes a discrete element method (DEM) model to investigate the mechanism of the force variation in struts and diaphragm walls during excavation and progressive collapse based on the Nicoll Highway accident in Singapore. This study identifies dangerous time points, which occur after the excavation has reached a certain depth, leaving a layer of soil without a corresponding strut. At these points, the bottommost one or two installed struts and diaphragm wall are critical components that can trigger progressive collapse if they fail. To prevent this, two concepts are proposed and are validated by DEM simulation. The sparse upper and dense lower (SUDL) strut arrangement concept ensures progressive collapse resistance of the retaining structure at the bottom of the excavation. The concept of dynamic redundant struts (DRSs) utilizes redundant struts to provide temporary protection in the vulnerable sections of the retaining system during excavation. Alternating the installation and removal of DRSs creates dynamic redundancy, ensuring progressive collapse resistance throughout the construction process in a relatively economical way. Additionally, the DRSs can effectively reduce the lateral deflection of the retaining wall.

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

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

Research on Outdoor Mobile Music Speaker Battery Management Algorithm Based on Dynamic Redundancy

In terms of the battery management system of a mobile music speaker, reliability optimization has always been an important topic. This paper proposes a new dynamic redundant battery management algorithm based on the existing fault-tolerant structure of a lithium battery pack. The internal configuration is adjusted according to the SOC of each battery, and the power supply battery is dynamically allocated. This paper selects four batteries to experiment on with two different algorithms. The simulation results show that compared with the traditional battery management algorithm, the dynamic redundant battery management algorithm extends the battery pack working time by 18.75%, and the energy utilization rate of B1 and B4 increases by 96.0% and 99.8%, respectively. This proves that the dynamic redundant battery management algorithm can effectively extend battery working time and improve energy utilization.

Методические основы синтеза моделей развития горных работ для управления процессом воспроизводства очистного фронта угольных шахт

This article presents the results of optimizing the reliability and reliability of the time forecast’s development reserves of the coal mine long wall areas and the preparation time of the face longwall line. A scheme of the reproduction the long wall front process in the form of a decision tree model has been developed. The dependences of the optimal probability of the absence of coal mining losses and the optimal dynamic time reserve on the reliability of longwall and preparatory work and on the ratio of damage in case of shortage, as well as the costs of maintaining the cleaning front, are established. It is shown that when forming a mining development plan, the value of the optimal dynamic time reserve should be determined for each treatment face. It is determined that when providing dynamic redundancy of the process of reproduction of the longwall front, the possibilities of performing degassing and drainage of mineral reserves being prepared for extraction are more fully realized which positively affects the level of reliability and safety of longwall operations.

Increasing safety levels in human-machine interaction by beyond-5G wireless redundancy

Factory automation in the context of Industry 4.0/5.0 requires safety levels to satisfy more stringent and tight limits than those available so far. This goal is further challenged by the extension to the wireless environment of industrial shop floor communications that were traditionally based on cabled networks. Starting with wireless LANs, the trend towards the use of industrial wireless is fostered by the advent of fifth Generation (5G) private connectivity and is bound to increase its pace in the evolution towards 6G. In particular, the interaction of human operators with industrial robots and autonomous vehicles on the shop floor is posing stringent safety requirements that in turn push forward the dependability and reliability limits of wireless connectivity. To help achieve these limits, this paper proposes a dynamic redundancy mechanism based on the real-time activation/deactivation of radio bearers instantiated between mobile devices carried by humans and machines and multiple base stations, to achieve guaranteed upper bounds on packet loss probability in the communication of data related to operational safety control loops. An optimization problem is posed, and suitable heuristics are evaluated by simulation in a 5G and beyond wireless environment, aiming to dynamically maintain the required reliability levels with small computational effort.

A Novel Virtual Sensor Modeling Method Based on Deep Learning and Its Application in Heating, Ventilation, and Air-Conditioning System

Realizing the dynamic redundancy of sensors is of great significance to ensure the energy saving and normal operation of the heating, ventilation, and air-conditioning (HVAC) system. Building a virtual sensor model is an effective method of redundancy and fault tolerance for hardware sensors. In this paper, a virtual sensor modeling method combining the maximum information coefficient (MIC) and the spatial–temporal attention long short-term memory (STA-LSTM) is proposed, which is named MIC-STALSTM, to achieve the dynamic and nonlinear modeling of the supply and return water temperature at both ends of the chiller. First, MIC can extract the influencing factors highly related to the target variables. Then, the extracted impact factors via MIC are used as the input variables of the STA-LSTM algorithm in order to construct an accurate virtual sensor model. The STA-LSTM algorithm not only makes full use of the LSTM algorithm’s advantages in handling historical data series information, but also achieves adaptive estimation of different input variable feature weights and different hidden layer temporal correlations through the attention mechanism. Finally, the effectiveness and feasibility of the proposed method are verified by establishing two virtual sensors for different temperature variables in the HVAC system.

Обеспечение отказоустойчивости в многомашинных вычислительных системах дистанционного зондирования Земли при ограниченных аппаратурных ресурсах

The paper centers on the problems of developing failure- and fault-tolerant systems for Earth remote sensing satellite constellation control. The study defines the concept of a complex that fail-safely performs a target task, in this case, the task of detecting a target event and monitoring its behavior and development, i.e. monitoring the target event, and gives a hierarchical satellite constellation structure. Findings of the research show that it is necessary to use dynamic redundancy, which can significantly increase the trajectory of self-controlled degradation and, accordingly, the satellite constellation active life. The complexity of the problem lies in ensuring the reliability of the results obtained when a large number of target events, both natural and man-caused, occur. The study introduces an approach to reduce hardware redundancy, i.e. monitor a larger number of events using a lower power satellite constellation, and proves that is possible to use the approach without losing the system reliability.

Designing of fault-tolerant computer system structures using residue number systems

AbstractThis article discusses computing systems that operate in residue number systems (RNSs). The main direction of improving computer systems (CSs) is increasing the speed of implementation of arithmetic operations and the reliability of their functioning. Encoding data in RNS solves the problem of optimal redundancy, i.e., the creation of such computing systems provides maximum reliability with restrictions on weight and size characteristics. This article proposes new structures of fault-tolerant CSs operating in RNS in the case of the application with an active fault-tolerant method. The use of the active fault-tolerant method (dynamic redundancy) in the RNSs provides higher reliability. In addition, with an increase in the digits of CSs, the efficiency of using the proposed structures increases.

Alterations of dynamic redundancy of functional brain subnetworks in Alzheimer’s disease and major depression disorders

The human brain is not only efficiently but also “redundantly” connected. The redundancy design could help the brain maintain resilience to disease attacks. This paper explores subnetwork-level redundancy dynamics and the potential of such metrics in disease studies. As such, we looked into specific functional subnetworks, including those associated with high-level functions. We investigated how the subnetwork redundancy dynamics change along with Alzheimer’s disease (AD) progression and with major depressive disorder (MDD), two major disorders that could share similar subnetwork alterations. We found an increased dynamic redundancy of the subcortical-cerebellum subnetwork and its connections to other high-order subnetworks in the mild cognitive impairment (MCI) and AD compared to the normal control (NC). With gained spatial specificity, we found such a redundancy index was sensitive to disease symptoms and could act as a protective mechanism to prevent the collapse of the brain network and functions. The dynamic redundancy of the medial frontal subnetwork and its connections to the frontoparietal subnetwork was also found decreased in MDD compared to NC. The spatial specificity of the redundancy dynamics changes may provide essential knowledge for a better understanding of shared neural substrates in AD and MDD.

Lightweight Dynamic Redundancy Control with Adaptive Encoding for Server-based Storage

With the recent performance improvements in commodity hardware, low-cost commodity server-based storage has become a practical alternative to dedicated-storage appliances. Because of the high failure rate of commodity servers, data redundancy across multiple servers is required in a server-based storage system. However, the extra storage capacity for this redundancy significantly increases the system cost. Although erasure coding (EC) is a promising method to reduce the amount of redundant data, it requires distributing and encoding data among servers. There remains a need to reduce the performance impact of these processes involving much network traffic and processing overhead. Especially, the performance impact becomes significant for random-intensive applications. In this article, we propose a new lightweight redundancy control for server-based storage. Our proposed method uses a new local filesystem-based approach that avoids distributing data by adding data redundancy to locally stored user data. Our method switches the redundancy method of user data between replication and EC according to workloads to improve capacity efficiency while achieving higher performance. Our experiments show up to 230% better online-transaction-processing performance for our method compared with CephFS, a widely used alternative system. We also confirmed that our proposed method prevents unexpected performance degradation while achieving better capacity efficiency.

On distributed object storage architecture based on mimic defense

With the advent of the era of big data, cloud computing, Internet of things, and other information industries continue to develop. There is an increasing amount of unstructured data such as pictures, audio, and video on the Internet. And the distributed object storage system has become the mainstream cloud storage solution. With the increasing number of distributed applications, data security in the distributed object storage system has become the focus. For the distributed object storage system, traditional defenses are means that fix discovered system vulnerabilities and backdoors by patching, or means to modify the corresponding structure and upgrade. However, these two kinds of means are hysteretic and hardly deal with unknown security threats. Based on mimic defense theory, this paper constructs the principle framework of the distributed object storage system and introduces the dynamic redundancy and heterogeneous function in the distributed object storage system architecture, which increases the attack cost, and greatly improves the security and availability of data.

Minimum attribute reduction algorithm based on quick extraction and multi-strategy social spider optimization

Intelligent optimization algorithm combined with rough set theory to solve minimum attribute reduction (MAR) is time consuming due to repeated evaluations of the same position. The algorithm also finds in poor solution quality because individuals are not fully explored in space. This study proposed an algorithm based on quick extraction and multi-strategy social spider optimization (QSSOAR). First, a similarity constraint strategy was called to constrain the initial state of the population. In the iterative process, an adaptive opposition-based learning (AOBL) was used to enlarge the search space. To obtain a reduction with fewer attributes, the dynamic redundancy detection (DRD) strategy was applied to remove redundant attributes in the reduction result. Furthermore, the quick extraction strategy was introduced to avoid multiple repeated computations in this paper. By combining an array with key-value pairs, the corresponding value can be obtained by simple comparison. The proposed algorithm and four representative algorithms were compared on nine UCI datasets. The results show that the proposed algorithm performs well in reduction ability, running time, and convergence speed. Meanwhile, the results confirm the superiority of the algorithm in solving MAR.

Reliability analysis on the train control system in the CTCS-3 operating mode

Purpose This paper aims to study the reliability of the high-speed train operation control system in the Chinese Train Control System Level 3 (CTCS-3) operating mode. Design/methodology/approach Dynamic fault tree and Bayesian network method are adopted to analyze the reliability and weakness of the CTCS-3 system. Findings First, a physical architecture and data flow diagram of the CTCS-3 system are established according to the typical structure and functions of the CTCS-3 system. Second, the dynamic fault tree of the CTCS-3 system is constructed. Considering the prior probability of the bottom event and the existence of dynamic redundancy, the dynamic fault tree is transformed into a Bayesian net. The reliability of the CTCS-3 system is carried out based on the prior probability and the weakness that affects the reliability of the system based on the posterior probability is also analyzed by the Bayesian network. Finally, it is disclosed that the impact of the on-board subsystem on the reliability of the CTCS-3 system is generally greater than that of the ground subsystem. The two weakest modules in the onboard subsystem are the driver-machine interface (DMI) and balise transmission module (BTM) and the weakest one in the ground subsystem is Balise. The analysis results are generally consistent with the malfunctions in the field operation of China’s high-speed railway. Originality/value (1) By reasoning, the reliability of the train operation control system in the CTCS-3 operating mode meets the standard requirements. (2) Through backward reasoning, it is found that the failure of the onboard subsystem leads to a greater probability of failure of the train control system. (3) The DMI, BTM and automatic train protection computer unit modules are weak components in the onboard subsystem. Vital digit input&output, train interface unit and train security gateway are rarely involved in previous research, the result in this paper shows that these three modules are also weak components in the subsystem, which requires attention.

MimicCloudSim: An environment for modeling and simulation of mimic cloud service

In recent years, an increasing number of application services are deployed in the cloud. However, the cloud platform faces unknown security threats brought by its unknown vulnerabilities and backdoors. Many researchers have studied the Cyber Mimic Defense (CMD) technologies of the cloud services. However, there is a shortage of tools that enable researchers to evaluate their newly proposed cloud service CMD mechanisms, such as scheduling and decision mechanisms. To fill this gap, we propose MimicCloudSim as a mimic cloud service simulation system based on the basic functionalities of CloudSim.MimicCloudSim supports the simulation of dynamic heterogeneous redundancy (DHR) structure which is the core architecture of CMD technology, and provides an extensible interface to help researchers implement new scheduling and decision mechanisms. In this paper, we firstly describes the architecture and implementation of MimicCloudSim, and then discusses the simulation process. Finally, we demonstrate the capabilities of MimicCloudSim by using a decision mechanism. In addition, we tested the performance of MimicCloudSim, the conclusion shows that MimicCloudSim is highly scalable.

Run-Time Recovery and Failure Analysis of Time-Triggered Traffic in Time Sensitive Networks

Reliability is one of the major concerns of Time Sensitive Networking (TSN). Current systems mostly rely on static redundancy to protect functionality from permanent component failures. This greatly increases the cost of Time-Triggered (TT) flows. Instead, Software Defined Networking (SDN) enables dynamic redundancy. Disrupted traffic can be rerouted by a centralized controller to reduce the cost while maintaining reliability. This paper presents an approach to compute alternative paths at run-time and analyze their impact on reliability. We define a novel three-mode recovery scheme, which includes full functionality, reduced functionality, and emergency halt modes. Run-time recovery for TT flows is explored using Integer Linear Programming (ILP) and a heuristic algorithm. Then, a Markov chain-based design-time reliability analysis is developed to evaluate the Mean Time to Reduced Functionality Mode (MTTRF) and Mean Time to Failure (MTTF) of run-time recoverable systems. Our experiments show that run-time recovery provides better protection against multi-point failures than static redundancy. Compared with the state of the art, our proposed ILP has better routing efficiency. The proposed heuristic algorithm can perform routing and scheduling in polynomial time, but it tends to route multicast flows to longer paths than ILP. Furthermore, when applied to realistic recovery scenarios, our proposed ILP improves the MTTF by up to 2× and the average execution time by up to 20× than the raw ILP of the state of the art. Although less efficient with multicast flows, the heuristic algorithm achieves similar reliability as the ILP, and its worst-case recovery time is below 100ms on an embedded ARM processor.

Collision detection and inverse dynamics control of KUKA LBR IIWA robot

This paper presents a collision reaction system and a controller based on inverse dynamics for KUKA IIWA LWR robot. Since it is widely used, a collision avoidance system is essential to ensure safety while working with this robot. The collision detection system presented monitors the working of the robot and as soon as a collision happens, it stops the system. The reaction strategies are invoked once a collision is detected, and they generate a counter torque which prevents the robot from colliding further with the obstacles in its path. Further, the collision avoidance system is called which generates a different joint trajectory while preserving the end-effector trajectory using dynamic redundancy resolution. An inverse dynamics-based closed-loop controller was created for this robot which was verified using the plots of actual vs. desired trajectory. The collision detection and reaction results are also presented. A suitable reaction strategy for collision reaction and avoidance was found by this analysis.

Propuesta de un sistema de comunicación inalámbrico para una red de sensores bajo el agua en tiempo real aplicado a un sistema ROV

This work a novel approach in radio frequency communications applied to a underwater wireless sensors network UWSN is presented. The proposal is to manipulate in a bounded and controlled environment a Remote Operated Vehicle ROV without umbilical cable through a underwater sensors network based on radio frequency communication, taking advantage of the faculties of this underwater communication in conjunction with a sensor network, furter, a dynamic redundancy is used in the transmitters towards the ROV to increasing the range and avoiding communication loss, aditional a static redundancy is applied on the receiver to increase te reliability of comunication. The part of the ROV receiving sensors is based on a statisc redundancy of 3 sensors which will apply a vote taking in order to failure tolerantce, the sensor network will applied a dinamic redundacy in the transmitters in order to follow the communication with the ROV, in case of failure, the communication loss can be compensated with another sensor of the network that will take its role.

Semiring optimizations: dynamic elision of expressions with identity and absorbing elements

This paper describes a compiler optimization to eliminates dynamic occurrences of expressions in the format a ← a ⊕ b ⊗ c . The operation ⊕ must admit an identity element z , such that a ⊕ z = a . Also, z must be the absorbing element of ⊗, such that b ⊗ z = z ⊗ c = z . Semirings where ⊕ is the additive operator and ⊗ is the multiplicative operator meet this contract. This pattern is common in high-performance benchmarks—its canonical representative being the multiply-add operation a ← a + b × c . However, several other expressions involving arithmetic and logic operations satisfy the required algebra. We show that the runtime elimination of such assignments can be implemented in a performance-safe way via online profiling. The elimination of dynamic redundancies involving identity and absorbing elements in 35 programs of the LLVM test suite that present semiring patterns brings an average speedup of 1.19x (total optimized time over total unoptimized time) on top of clang -O3. When projected onto the entire test suite (259 programs) the optimization leads to a speedup of 1.025x. Once added onto clang, semiring optimizations approximates it to TACO, a specialized tensor compiler.

MEMS gyroscope fault detection and elimination for an underwater robot using the combination of smooth switching and dynamic redundancy method

Micro Electro Mechanical System (MEMS) gyroscope sensors are used in different underwater vehicles to determine their attitude as the input of the controller system to adjust the attitude to the desired value. Fault detection and elimination are necessary for MEMS gyroscope sensors to avoid disruption of the system performance. In this paper, it is tried to study different types of gyroscope sensor faults which can be detected and eliminated by designing a new proposed dynamic redundancy scheme. The proposed method is consisted of two MEMS gyroscope sensors and is modified by considering underwater robot dynamics in threshold tuning via Monte Carlo simulations. The switch between the primary and secondary gyroscope sensors is designed by smoothing methods to eliminate undesirable behavior of switching kick. Finally, numerical and experimental simulations are performed by a three degree of freedom table to show that the proposed method is efficient for the underwater robot exposed to gyroscope sensor faults.