Fault-tolerant Approach Research Articles

Fault Tolerance Model for Hadoop Distributed System

Fault tolerance approaches in distributed systems are essentially based on replication and checkpointing. Each of these approaches has its advantages and limitations. This paper has two objectives: first, it proposes a fault tolerance approach based on the nodes status of a distributed system. For this purpose, it defines 3 nodes status: safety, faulty and potentially faulty. With respect of classical node status (safety, faulty), it introduces a new status that we call potentially faulty. This last node allows to enhance the availability of a distributed system. Second, it discusses the efficiency of the proposed model on two types of architectures: virtual multi-node cluster and a physical multi-node cluster with WIFI connection. Experiments have showed that proposed approach increases the system performance throughput and its fault tolerance level.

An integrated sensor fault estimation and fault tolerant control design approach for continuous-time switched systems

An integrated sensor fault estimation and fault tolerant control design approach for continuous-time switched systems

Systolic array-based CNN accelerator soft error approximate fault tolerance design

To satisfy the massive computational requirement of Convolutional Neural Networks, various Domain-Specific Architecture based accelerators have been deployed in large-scale systems. While improving the performance significantly, the high integration of the accelerator makes it much more susceptible to soft-error, which will be propagated and amplified layer by layer during the execution of CNN, finally disturbing the decision of CNN and leading to catastrophic consequences. CNNs have been increasingly deployed in security-critical areas, requiring more attention to reliable execution. Although the classical fault-tolerant approaches are error-effective, the performance/energy overheads introduced are non-negligible, which is the opposite of CNN accelerator design philosophy. In this article, we leverage CNN's intrinsic tolerance for minor errors and the similarity of filters within a layer to explore the Approximate Fault Tolerance opportunities for CNN accelerator fault tolerance overhead reduction. By gathering the filters into several check groups by clustering to perform an inexact check while ensuring that serious errors are mitigated, our approximate fault tolerance design can reduce fault tolerance overhead significantly. Furthermore, we remap the filters to match the checking process and the dataflow of systolic array, which can satisfy the real-time checking demands of CNN. Experimental results exhibit that our approach can reduce 73.39%performance degradation of baseline DMR.

A Linear Swarm – Based Intelligence for Resource Allocation and Fault Prediction in Cloud

The widespread utilization Cloud Computing (CC) services for hosting real-time applications have led to the appearance of service dependability as an essential issue in both users and Cloud Service Providers (CSP). Two diverse fault tolerant approaches are provided to improve the cloud service reliability known as proactive and reactive model. Various prevailing approaches consider the coordination problem among the Virtual Machines (VMs) executes parallel processing. Devoid of appropriate VM coordination, the parallel processing outcomes are not so appropriate. To handle this issue, a VM-based cluster allocation model is designed to diminish the total resource consumption by the data centers and network resources. Here, the VM migration process is performed for deteriorating PM to certain optimal PMs. At last, the optimal target selection is handled with an improved optimization approach known as linear Swarm-based intelligence. Here, various metrics are evaluated and compared with other approaches. The experimental outcomes illustrate the efficiency of the anticipated model.

Fault‐tolerance approaches for distributed and cloud computing environments: A systematic review, taxonomy and future directions

AbstractFault tolerance is crucial in ensuring smooth working of distributed and cloud computing. It is challenging to implement because of the constantly changing infrastructure and complex configurations in distributed and cloud computing. Implementation of various fault tolerance methods require domain‐specific knowledge as well as in‐depth understanding of the existing techniques and approaches. Recent surveys on fault tolerance in cloud and distributed environments exist, but they have limitations. This article systematically reviews fault tolerance approaches in distributed and cloud computing and discusses their taxonomy. Based on the taxonomy provided, fault‐tolerance approaches are divided into four types, that is, reactive approaches, proactive approaches, adaptive approaches, and hybrid approaches. Reactive approaches provide a preventive measure after the occurrence of faults in the system. Proactive approaches prevent the system or minimize failure effects by predicting in advance. The adaptive approaches predict, learn, and adapt the changes to deal with new faults in the system. The hybrid approaches combine reactive, proactive, and adaptive approaches. The objective of this article is to give a better understanding of handling faults using suitable approaches and further compare them on various parameters. The paper also presents a promising research direction based on the challenges and issues in multiple approaches.

Design and Analysis of a New Fault-Tolerant QCA-based Nano-Scale Circuit for Morphological Operations in Image Processing

Quantum-dot cellular automata (QCA) is based on traditional cellular automata models in which each cell has one of the finite distinct states at any given time. Cellular automata refer to the use of Coulombic contact rather than wires to connect cells. The discrete character of cellular automata and quantum mechanics have been exploited to develop nano-scale devices that can conduct computations with high switching frequency and low power dissipation. QCA has been utilized in many categories for fault-tolerant and reversible logic computing. On the other hand, the morphology algorithm is an area of image processing that provides a unified methodology and strong tools for image/video processing applications. This work proposes a unique fault-tolerant approach based on QCA to execute the morphological operations in image processing. Two fault-tolerant 5-input majority gates are employed in the implemented QCA architecture, and a control line is used to accomplish dilation and erosion. To assess the capabilities of the proposed fault-tolerant circuit for morphological procedures, its performance is analyzed and confirmed. The proposed design is compared to earlier results, which significantly improve fault-tolerant ability.

Design of fault tolerant algorithm for network on chip router using field programmable gate array

<p class="Abstract">Many internet protocol (IP) modules are present in contemporary system on chips (SoCs). This could provide an issue with interconnection among different IP modules, which would limit the system's ability to scale. Traditional bus-based SoC architectures have a connectivity bottleneck, and network on chip (NoC) has evolved as an embedded switching network to address this issue. The interconnections between various cores or IP modules on a chip have a significant impact on communication and chip performance in terms of power, area latency and throughput. Also, designing a reliable fault tolerant NoC became a significant concern. In fault tolerant NoC it becomes critical to identify faulty node and dynamically reroute the packets keeping minimum latency. This study provides an insight into a domain of NoC, with intention of understanding fault tolerant approach based on the XY routing algorithm for 4×4 mesh architecture. The fault tolerant NoC design is synthesized on Field programmable gate array (FPGA).</p>

Design and analysis of fault-tolerant sequential logic circuits for safety-critical applications

Safety-critical systems used in applications that demand high levels of dependability, efficiency, and fault-tolerance often use sequential logic circuits in its design and implementation. The safety-critical digital system typically uses latches, flip-flops, and other memory elements, which are prone to the effects of natural faults and single event upsets (SEUs) caused by radiation-induced effects. The faults can lead to subsystem failures due to the continuous advancement in the realization of the small size transistor. To design a reliable digital-based system, it is essential to develop new fault-tolerance approaches that are integrated into the design of sequential logic circuits. This work proposes a novel fault-tolerant approach based on the redundancy of sequential logic circuit, which consists of a variety of design components, D flip-flop storage elements linked to a fault injection unit, a duplicate modular redundancy, and data monitoring units with a switching circuit. The experimental simulation results using a five-state Markov chain analysis model prove that the proposed fault-tolerant system can achieve 0.99999998 for reliability of the fault detection coverage (C) which equal to 0.99999. Finally, we believe that using this new approach of fault-tolerance and redundancy would improve the dependability and reliability of next generation safety-critical applications.

Fault‐resilient control of parallel PV inverters using multi‐agent twin‐delayed deep deterministic policy gradient approach

SummaryGrid‐tied photovoltaic system (GTPS) are widely favored due to their inherent benefits. The interface of parallel power electronic converters in these systems is rapidly increasing. The inverter in GTPS has a very important role in power conversion, transfer, and control. However, their challenging working conditions contribute to susceptibility to power switching device failures. Traditional fault diagnosis and tolerant approaches exhibit limitations in control efficiency, model dependency, and slow recovery from fault. This study proposes a multi‐agent twin delayed deep deterministic policy gradient (MATD3PG) configuration for intelligent parallel inverter control, fault diagnosis, and fault‐tolerant operation in GTPS structure. By leveraging the multi‐agent reinforcement learning (RL) framework, an optimal control of the parallel inverter can be achieved, encompassing fault‐tolerant operation using MATLAB Simulink/PLECS. The major advantage the given technique offers is that it carries out optimum fault‐tolerant operation without causing the system derating. Experimental findings demonstrate that the proposed fault‐tolerant model based on RL traditional methods is able to ensure continuous supply to the connected loads even during fault events. Further, the transition time from fault occurrence to recovery is found to be 6 ms, which is quite less compared with the fault‐tolerant techniques presented in literature. Through real‐time fault diagnosis‐based results, the proposed approach ensures precise tracking of reference currents, quicker response times, uninterrupted supply, and smooth transition to the post‐fault operation mode.

A resilient approach for simultaneous fault detection and control for a class of nonlinear systems

The simultaneous fault detection and control (SFDC) has emerged as a reliable scheme. However, what happens when the designed structure undergoes changes? Such variations have the potential to cause instability and misdiagnosis. This paper delves into a cutting-edge SFDC structure that surpasses conventional designs in terms of reliability. The proposed Resilient Simultaneous Fault Detection and Control (RSFDC) structure considers variations in the designed parameters and provides a more robust and fault-tolerant approach to SFDC, with important implications for the design of reliable and resilient control systems in a broad range of applications. This scheme is formulated as a multi-objective optimisation problem, encompassing control and diagnosis objectives. Specifically, it aims to minimise the impact of faults and disturbances on the controlled output while reducing residual sensitivity to all changes and maximising the fault effects on the residual. Through simulation comparisons, this paper showcases the merits of the RSFDC structure in two examples, highlighting its superiority over other designs.

A fault tolerance aware green IoT workflow scheduling algorithm for multi-dimensional resource utilization in sustainable cloud computing

In recent times, the distributed cloud computing landscape has witnessed a remarkable surge in processing vast amounts of data and the crucial need to maintain service level agreements (SLAs) between providers and consumers. In this dynamic environment, cloud resources are inherently multidimensional, encompassing computing machines and communication connections susceptible to failures and energy-related considerations. However, given two-objective energy and reliability optimization, existing time allocation policies focus primarily on optimizing a single intent, which leads to system degradation in environments that generate problematic constraints from executable processing units. To handle the shortcomings of the application placement policies, we suggest a solution in the form of a three-phase bi-objective workflow scheduling issue called (Bi-OWSP). This three-phase approach aims to optimize workflow scheduling by simultaneously considering energy and reliability as two vital objectives. To achieve this, we employ two distinct algorithms. First is the stepwise dynamic voltage and frequency scale algorithm ensures energy efficiency by calculating optimal frequencies, reducing energy usage, and minimizing task mapping time. The second algorithm is the reliability-conscious heterogeneous fault tolerance approach, which emphasizes avoiding high-deficit servers and communication links to enhance system reliability. Furthermore, we introduce an energy-aware stepwise reliability maximization algorithm, which intelligently selects the best combination of task-server pairs to achieve energy minimization and reliability maximization. Through extensive simulation experiments on artificial and real-world workflow applications, we demonstrate the significance of Bi-OWSP in providing superior energy-reliability compensation solutions compared to competing algorithms.

Twin model-based fault detection and tolerance approach for in-core self-powered neutron detectors

Twin model-based fault detection and tolerance approach for in-core self-powered neutron detectors

Software Fault Tolerance in Real-Time Systems: Identifying the Future Research Questions

Tolerating hardware faults in modern architectures is becoming a prominent problem due to the miniaturization of the hardware components, their increasing complexity, and the necessity to reduce costs. Software-Implemented Hardware Fault Tolerance approaches have been developed to improve system dependability regarding hardware faults without resorting to custom hardware solutions. However, these come at the expense of making the satisfaction of the timing constraints of the applications/activities harder from a scheduling standpoint. This article surveys the current state-of-the-art of fault tolerance approaches when used in the context of real-time systems, identifying the main challenges and the cross-links between these two topics. We propose a joint scheduling-failure analysis model that highlights the formal interactions among software fault tolerance mechanisms and timing properties. This model allows us to present and discuss many open research questions with the final aim to spur future research activities.

Integrating request replication into FaaS platforms: an experimental evaluation

Function-as-a-Service (FaaS) is a popular programming model for building serverless applications, supported by all major cloud providers and many open-source software frameworks. One of the main challenges for FaaS providers is providing fault tolerance for the deployed applications, that is, providing the ability to mask failures of function invocations from clients. The basic fault tolerance approach in current FaaS platforms is automatically retrying function invocations. Although the retry approach is well suited for transient failures, it incurs delays in recovering from other types of failures, such as node crashes. This paper proposes the integration of a Request Replication mechanism in FaaS platforms and describes how this integration was implemented in Fission, a well-known, open-source platform. It provides a detailed experimental comparison of the proposed approach with the retry approach and an Active-Standby approach in terms of performance, availability, and resource consumption under different failure scenarios.

Active fault-tolerant control of quadrotor UAVs with nonlinear observer-based sliding mode control validated through hardware in the loop experiments

Multirotor unmanned aerial vehicles (UAV) are highly prone to motor faults, which can arise from defective motors or damaged propellers. Motor faults severely change the multirotor UAV’s dynamics and therefore endanger flight safety and reliability since the controller loses its efficiency. To cope with such crucial problems, a fault-tolerant controller is proposed in this paper for full control of a quadrotor UAV with motor faults. The proposed fault-tolerant approach consists of the nonlinear observer technique and the Sliding Mode Control (SMC). The designed novel nonlinear observer predicts the effects of motor faults on quadrotor dynamics and it is augmented with an SMC to create a fault-tolerant controller. In addition, the nonlinear observer enhances the robustness of the SMC against the uncertainties and disturbances acting on the quadrotor during flight. Any actuator fault will be treated as a disturbance detected by the nonlinear observer and will be attenuated directly by the proposed SMC. The disturbance attenuation capability achieved by the nonlinear observer decreases the amount of control action expected from the SMC, which results in advanced robustness without sacrificing the nominal control performance. The performance of the proposed nonlinear observer SMC (NOSMC) is demonstrated through simulations and testbed experiments. The results show that the proposed fault-tolerant controller effectively recovers the full control of the quadrotor with motor faults up to 40% while tracking the predefined trajectory and rotation angles as desired.

Failure Identification Method and LMI-Based Control System for Small Spacecraft

This study aimed to design a linear matrix inequality (LMI)-based robust control system and a failure identification method for small spacecraft. The key feature of the proposed method is its capability to withstand failure in the actuation system by means of the observer and controller gain definition. An effective approach for withstanding failure is required due to the small capabilities of the momentum exchange device (MED) and the system’s sensitivity to external perturbations. Passive fault-tolerant approaches can be included in the design process of the control algorithm. In particular, the main objective of this study was the design of an H∞ controller that started from an LMI formulation and considered the parametric uncertainties and matched failure of the actuation system. In addition, a fault detection method based on sliding mode observers was proposed to include an active disturbance correction algorithm and improve the system robustness and performance during spacecraft stabilization. The closed-loop system was evaluated for different initial conditions, including attitude positions that are far from the desired condition. The effectiveness of the proposed approach was demonstrated using extensive simulations that considered a pyramidal actuation configuration and hardware constraints.

Coordinated Distributed Predictive Control for Voltage Regulation of DC Microgrids With Communication Delays and Data Loss

This paper is concerned with the voltage tracking problem of DC microgrids subject to communication delays and packet losses, for which existing work commonly adopts passive fault-tolerant approaches. To accurately compensate for the above communication constraints experienced by DC microgrids, a coupled discrete microgrid model is developed on the basis of the physical laws of actual DC microgrids. Unlike the practice of passively tolerating communication delays, through the physical model established, this paper suggests a consensus-based proportional-integral predictive control strategy, which can actively compensate for communication delays and consecutive packet dropouts encountered by DC microgrids. Under the observer-based distributed networked predictive control framework, each distributed generation subsystem in the microgrid exchanges its own measurements over the network and integrates information from controllers of other units to achieve output voltage consensus in the presence of time delays and packet losses. Furthermore, to demonstrate the generality of the proposed method, the sufficient and necessary conditions for the DC microgrid system to accomplish voltage tracking are given. These conditions are rendered in the form of matrix eigenvalues associated with the physical connections and communication couplings between distributed generation units. Besides, the stability and convergence of the closed-loop microgrid system are given in the form of linear matrix inequality based on the Lyapunov function. Finally, the performance of the proposed control scheme is evaluated in terms of its convergence, robustness to load variations, and plug-and-play functionality through the built photovoltaic cell-based (with battery banks) DC microgrid hardware system.

A Systematic Literature Review of Unsupervised Fault Detection Approach for Complex Engineering System

Monitoring complex engineering systems is an important countermeasure in managing the risk of faulty events. Observing the response of each process flow will avoid further damages in the production cycle. Both fault-tolerant approach that bears with faulty events and scheduled maintenance that helps to reduce tool wearing are deeply involved in condition-based monitoring methods implemented in factories. Thus, identification of faulty equipment is need to avoid major breakdown in the production system. A classification framework shows good performance in classifying faulty events, but a labelled dataset is usually financially consuming. Machine learning (ML) techniques have become a prospective tool in the unsupervised fault detection (UFD) approach to prevent total failures in complex engineering system. However, the efficiency of UFD applications, on the other hand, is determined by the selected ML method. This paper presents a systematic literature review of ML methods applied for UFD, highlighting the methods explored in this field and the success of today's state-of-the-art machine learning techniques. This review focuses on the Scopus scientific database and provides a useful information on ML techniques, challenges and opportunities, and new research works in the UFD field.

A Novel SVPWM Fault-Tolerant Strategy for Torque Ripple Reduction of Seven-Phase Induction Machines Under Single-Phase Open-Circuit Fault

The development of multiphase drives has taken on an accelerated pace in the last decades, and fault-tolerance has been the subject of many classic studies. Traditional space vector pulsewidth modulation (SVPWM) would cause significant torque ripple in the case of open-circuit fault, which in turn degrades the fault-tolerant performance of multiphase machines. This work proposes a novel SVPWM fault-tolerant strategy for seven-phase induction machine under a single-phase open-circuit fault. A deeper insight has been provided into the reconstruction of voltage vectors without using reference current, ensuring the generality for various fault-tolerant principles. Subsequently, an eight-sector-based sector division method is proposed, and five specific nonzero voltage vectors and two zero-voltage vectors in each sector are determined to be candidates. Without confliction of switching state, the symmetric modulation module can still be utilized, which will minimize the modifications after fault occurrence. Besides, the close-loop control for harmonic planes can be fulfilled. Finally, experimental results have demonstrated the effectiveness of the proposed SVPWM fault-tolerant approach under both steady and transient states.

Seamless Fault-Tolerant Control for Cascaded H-bridge Converters Based Battery Energy Storage System

This article presents a phase-shifted pulsewidth-modulation-based fault-tolerant approach for the cascaded H-bridge-based battery energy storage system to ride through the single switch fault. When the fault occurs, the faulty cell is bypassed first. Afterwards, the missing voltage levels of the faulty cell are compensated by the remaining healthy cells to maintain the line-to-line voltages balanced. The compensation of the missing voltage levels presented is achieved by simple logic operation without modifying three-phase voltage references and phase-shifted angles of carriers, which enables seamless operation and enhances the system stability. In addition, the detailed active power control strategy used for state-of-charge balancing of the battery units is proposed and discussed. The validity and effectiveness of the proposed method are verified by simulation and experimental results.