Fault Tolerance Aspects Research Articles

Fault tolerance challenges in wearable computing for vital applications: a survey

Wearable computers can be used in different domains including healthcare. However, due to suffering from challenges such as faults their applications may be limited in real practice. So, in designing wearable devices, designer must take into account fault tolerance techniques. This study aims to investigate the challenging issues of fault tolerance in wearable computing. For this purpose, different aspects of fault tolerance in wearable computing namely hardware, software, energy, and communication are studied; and state of the art research regarding each category is analysed. In this analysis, the performed works using the fault tolerance techniques are included in the form of 25 components and referred to as “fault tolerance plan”. Using this fault tolerance plan and the appropriate profile, the fault tolerance of any wearable system can be evaluated. In this article, fault tolerances of several of the most prominent works conducted in the field of wearable computing were evaluated. The obtained results, with the medical profile, showed that only one wearable system had a fault tolerance of 91%, with the other systems having a fault tolerance of 24% or less. Also, the results obtained from evaluating these works, with the military profile, showed that only one wearable system had a fault tolerance of 76%, with the other systems having a fault tolerance of 19% or less. These mean that few studies have been conducted on the fault tolerance of wearable computing.

Extending rely-guarantee thinking to handle real-time scheduling

The reference point for developing any artefact is its specification; to develop software formally, a formal specification is required. For sequential programs, pre and post conditions (together with abstract objects) suffice; rely and guarantee conditions extend the scope of formal development approaches to tackle concurrency. In addition, real-time systems need ways of both requiring progress and relating that progress to some notion of time. This paper extends rely-guarantee ideas to cope with specifications of—and assumptions about—real-time schedulers. Furthermore it shows how the approach helps identify and specify fault-tolerance aspects of such schedulers by systematically challenging the assumptions.

Redactable consortium blockchain based on verifiable distributed chameleon hash functions

With the evolving application demands, the inherent immutability of consortium blockchains hinders their widespread adoption. For example, expired data stored on the chain cannot be deleted, and erroneous data cannot be redacted, seriously limiting the flexibility of consortium blockchains. However, existing redactable blockchain solutions need to be improved in aspects of decentralization, efficiency, and fault tolerance. This paper develops a new verifiable distributed chameleon hash (VDCH) function to solve the above problems. With VDCH, nodes share chameleon keys with a secure multi-party computation protocol based on a verifiable key-sharing scheme, and the collision shares can be verified with a Schnorr non-interactive zero-knowledge proof protocol, which enhances the fault tolerance of the consortium chain while maintaining its decentralized nature. Then, this paper proposes a consensus protocol called CVTSS based on verifiable threshold signatures, which provides protocol support for collaborative hash collision computation by multiple nodes using VDCH, thus avoiding the dependence on Nakamoto consensus and improving the redaction efficiency. Meanwhile, CVTSS uses threshold signatures to prevent malicious nodes from tampering with data using one-time chameleon keys. Finally, this paper constructs an efficient, practical, and secure redactable consortium chain scheme based on VDCH and CVTSS. Theoretical analysis and experimental results show that the proposed scheme can operate safely in the presence of malicious nodes with an acceptable time cost.

A novel self-healing model using precoding & big-data based approach for 5G networks

The study of self organized networks is considered a key element in developing the new generation of cellular networks. Mobile service providers are adopting new technologies such as small cells and precoding to deploy their networks according to 5G standards. As these type of technologies gain more importance and popularity, network self organization become a more essential function in operating the network resources. Self organized networks have been classified into three main categorizes: self optimization, self configuration, and self healing. The first two categories showed further development and research interest when compared to self-healing. Due to the high density nature of small cells, using massive antennas in the network, and their susceptibility to failures for various reasons, the demand for a clear self-healing process and architecture is deemed urgent. In this paper the current self-healing process in addition to the fault tolerance aspects for the future 5G are studied and a new process model for organizing the self-healing process is proposed. The new process model is meant to map the different functionalities needed to perform a successful self healing process. The model with the proposed descriptive network architecture aims to identify the different functions within the self-healing process model. In order to test the operation ability of the model, a new big data aspect is added to the network architecture to aid in analyzing the huge amount of data needed to efficiently perform the self-healing process. Results show that the proposed precoding technique in conjunction with the machine learning algorithm based on a decision tree model that uses empirical data collected from the network can identify the status of cells (healthy, congested or failing) and suitable self-healing procedures can be triggered to recover the cell accordingly.

Fault-tolerant quantum error correction on near-term quantum processors using flag and bridge qubits

Fault-tolerant (FT) computation by using quantum error correction (QEC) is essential for realizing large-scale quantum algorithms. Devices are expected to have enough qubits to demonstrate aspects of fault tolerance in the near future. However, these near-term quantum processors will only contain a small amount of noisy qubits and allow limited qubit connectivity. Fault-tolerant schemes that not only have low qubit overhead but also comply with geometrical interaction constraints are therefore necessary. In this work, we combine flag fault tolerance with quantum circuit mapping, to enable an efficient flag-bridge approach to implement FT QEC on near-term devices. We further show an example of performing the Steane code error correction on two current superconducting processors and numerically analyze their performance with circuit level noise. The simulation results show that the QEC circuits that measure more stabilisers in parallel have lower logical error rates. We also observe that the Steane code can outperform the distance-3 surface code using flag-bridge error correction. In addition, we foresee potential applications of the flag-bridge approach such as FT computation using lattice surgery and code deformation techniques.

Fault-tolerant functional reactive programming (extended version)

Abstract Highly critical application domains, like medicine and aerospace, require the use of strict design, implementation, and validation techniques. Functional languages have been used in these domains to develop synchronous dataflow programming languages for reactive systems. Causal stream functions and functional reactive programming (FRP) capture the essence of those languages in a way that is both elegant and robust. To guarantee that critical systems can operate under high stress over long periods of time, these applications require clear specifications of possible faults and hazards, and how they are being handled. Modeling failure is straightforward in functional languages, and many functional reactive abstractions incorporate support for failure or termination. However, handling unknown types of faults, and incorporating fault tolerance into FRP, requires a different construction and remains an open problem. This work demonstrates how to extend an existing functional reactive framework with fault tolerance features. At value level, we tag faulty signals with reliability and probability information and use random testing to inject faults and validate system properties encoded in temporal logic. At type level, we tag components with the kinds of faults they may exhibit and use type-level programming to obtain compile-time guarantees of key aspects of fault tolerance. Our approach is powerful enough to be used in systems with realistic complexity, and flexible enough to be used to guide system analysis and design, validate system properties in the presence of faults, perform runtime monitoring, and study the effects of different fault tolerance mechanisms.

Open-circuit fault-tolerance in multilevel inverters with reduced component count

High component count and subsequent effects on volume and reliability have been the major concerns for practical applications of multilevel inverters (MIs). Recent emergence of the so-called reduced component count MIs (RCC-MIs) has been driven by the attempts to reduce the number of power switches for multilevel power conversion. In many of such topologies, the aspect of fault tolerance has not been given full consideration. In this work, some of the recently proposed RCC-MI topologies have been considered and analyzed in the light of imparting fault tolerance capability in the case of open-switch failure of any one of the power switches. In an RCC-MI, the occurrence of an open-circuit fault in a power switch would often lead to shut down due to the lack of redundant switching states. To overcome these occurrences, an optimal addition of power switches is described in this work so that the desired redundant states can be synthesized. The modified RCC-MI topologies so obtained have been analyzed under the normal and faulty conditions and computer simulations have been carried out using MATLAB/Simulink, and corresponding results have been presented. The results so obtained are experimentally validated to prove the feasibility of the proposed fault-tolerant topologies.

Reliable, Effective and Fault-Tolerant Design of LeafyCube Interconnection Network Topology

This paper attempts to derive the performance properties of the Leafycube (LC) interconnection network. The Leafycube is already observed to have quite superior topological properties in comparison to the other contemporary networks. The various performance parameters of the LC network are studied and compared with the existing HC and its variants. The routing and broadcasting algorithms are proposed and the time complexities are also compared. The paper attempts to evaluate the cost effectiveness, reliability and fault tolerance aspects of LC interconnection network in order to justify the novelty in the design of the proposed structure. The leafy structure helps to retain the original hypercube while improving the node packing density in the interconnection network.

Sustainable subway indoor air quality monitoring and fault-tolerant ventilation control using a sparse autoencoder-driven sensor self-validation

Sensors providing measurements for monitoring and control of indoor air quality (IAQ) are key components of the ventilation systems in subway stations. However, faulty sensors due to harsh ambient conditions may deliver incorrect information triggering misinterpretation; causing energy waste or IAQ deterioration. This paper presents a holistic online framework for sensor self-validation in a subway station based on a sparse autoencoder (AE) architecture. The sensor self-validation procedure consists of sensor fault detection, faulty sensor identification, and faulty sensor reconstruction. First, the AE-based detection rate between 44% and 100%. Then, the faulty sensor identification was conducted through an AE-sensor validity index (SVIAE). The faulty sensor reconstruction was conducted by the AE structure and evaluated with several performance metrics. Finally, the sustainability and fault-tolerance aspects of this framework were verified through mathematical modeling of the ventilation system; showing the effects of the faulty and reconstructed sensors on energy consumption and public health.

Research on logistics supply chain of iron and steel enterprises based on block chain technology

At present, the service trading system of steel logistics industry is highly centralized, with poor collaborative ability. Information flow, capital flow and logistics need to be certified by logistics center nodes. It cannot achieve information transparency, traceability and tampering, and the information security of customers cannot be effectively guaranteed. This has affected the information security, automation and intelligence of logistics enterprise service transactions. Firstly, this paper introduces the data layer, network layer and consensus layer in the block chain, and then establishes the steel logistics architecture under the block chain technology. Then, it analyzes the management of logistics information resources in the supply chain from the object, attribute and function dimensions. Finally, the improved PFBT algorithm is used to test their de-centralization security and algorithm performance in the system of iron and steel enterprise logistics transactions. The experimental comparison shows that the improved PBFT algorithm has been greatly improved in the aspects of algorithm security, algorithm delay, algorithm throughput and algorithm fault tolerance.

Evaluating VOML Framework as a Dependable System

Virtual Organizations (VOs) and Virtual Breeding Environments (VBEs) are resilient, dependable and fault-tolerant by virtue of being virtual in existence. In this article, Virtual Organization Modeling Language framework is evaluated against dependability and fault-tolerance aspects.

Prediction model of insulator contamination degree based on adaptive mutation particle swarm optimisation and general regression neural network

The contaminants accumulated on the surface of transmission line insulator mainly come from the suspended particles in the air. Therefore, it is necessary to consider meteorological factors and environmental factors in the prediction of insulator contamination degree. In view of the advantages of generalised regression neural network (GRNN) in the aspects of fault tolerance and robustness, this study uses it to predict equivalent salt deposit density (ESDD). Furthermore, the adaptive mutation particle swarm optimisation and GRNN prediction model is proposed in this study. According to adaptive algorithm and mutation algorithm, the inertia weight and acceleration factor of particles are dynamically adjusted to achieve the purpose of searching global optimal smoothing factor. The optimisation method can effectively avoid the premature convergence of particle swarm optimisation (PSO) and solve the drawback that PSO is easy to fall into the local optimal value. The results show that the prediction model proposed in this study can effectively predict the insulators ESDD, and the prediction error is less than the GRNN and PSO–GRNN models. The research can provide guidance for the development of a more scientific and rational maintenance plan to achieve effective control of the contaminants of the line.

Fault tolerant functional reactive programming (functional pearl)

Highly critical application domains, like medicine and aerospace, require the use of strict design, implementation and validation techniques. Functional languages have been used in these domains to develop synchronous dataflow programming languages for reactive systems. Causal stream functions and Functional Reactive Programming capture the essence of those languages in a way that is both elegant and robust. To guarantee that critical systems can operate under high stress over long periods of time, these applications require clear specifications of possible faults and hazards, and how they are being handled. Modeling failure is straightforward in functional languages, and many Functional Reactive abstractions incorporate support for failure or termination. However, handling unknown types of faults , and incorporating fault tolerance into Functional Reactive Programming, requires a different construction and remains an open problem. This work presents extensions to an existing functional reactive abstraction to facilitate tagging reactive transformations with hazard tags or confidence levels. We present a prototype framework to quantify the reliability of a reactive construction, by means of numeric factors or probability distributions, and demonstrate how to aid the design of fault-tolerant systems, by constraining the allowed reliability to required boundaries. By applying type-level programming, we show that it is possible to improve static analysis and have compile-time guarantees of key aspects of fault tolerance. Our approach is powerful enough to be used in systems with realistic complexity, and flexible enough to be used to guide their analysis and design, to test system properties, to verify fault tolerance properties, to perform runtime monitoring, to implement fault tolerance during execution and to address faults during runtime. We present implementations in Haskell and in Idris.

Fault tolerant multi-sensor fusion based on the information gain

In the last decade, multi-robot systems are used in several applications like for example, the army, the intervention areas presenting danger to human life, the management of natural disasters, the environmental monitoring, exploration and agriculture. The integrity of localization of the robots must be ensured in order to achieve their mission in the best conditions. Robots are equipped with proprioceptive (encoders, gyroscope) and exteroceptive sensors (Kinect). However, these sensors could be affected by various faults types that can be assimilated to erroneous measurements, bias, outliers, drifts,… In absence of a sensor fault diagnosis step, the integrity and the continuity of the localization are affected. In this work, we present a muti-sensors fusion approach with Fault Detection and Exclusion (FDE) based on the information theory. In this context, we are interested by the information gain given by an observation which may be relevant when dealing with the fault tolerance aspect. Moreover, threshold optimization based on the quantity of information given by a decision on the true hypothesis is highlighted.

Shannon information entropy in the canonical genetic code

The Shannon entropy measures the expected information value of messages. As with thermodynamic entropy, the Shannon entropy is only defined within a system that identifies at the outset the collections of possible messages, analogous to microstates, that will be considered indistinguishable macrostates. This fundamental insight is applied here for the first time to amino acid alphabets, which group the twenty common amino acids into families based on chemical and physical similarities. To evaluate these schemas objectively, a novel quantitative method is introduced based the inherent redundancy in the canonical genetic code. Each alphabet is taken as a separate system that partitions the 64 possible RNA codons, the microstates, into families, the macrostates. By calculating the normalized mutual information, which measures the reduction in Shannon entropy, conveyed by single nucleotide messages, groupings that best leverage this aspect of fault tolerance in the code are identified. The relative importance of properties related to protein folding - like hydropathy and size - and function, including side-chain acidity, can also be estimated. This approach allows the quantification of the average information value of nucleotide positions, which can shed light on the coevolution of the canonical genetic code with the tRNA-protein translation mechanism.

Quantum gates with controlled adiabatic evolutions

We introduce a class of quantum adiabatic evolutions that we claim may be interpreted as the equivalents of the unitary gates of the quantum gate model. We argue that these gates form a universal set and may therefore be used as building blocks in the construction of arbitrary `adiabatic circuits', analogously to the manner in which gates are used in the circuit model. One implication of the above construction is that arbitrary classical boolean circuits as well as gate model circuits may be directly translated to adiabatic algorithms with no additional resources or complexities. We show that while these adiabatic algorithms fail to exhibit certain aspects of the inherent fault tolerance of traditional quantum adiabatic algorithms, they may have certain other experimental advantages acting as quantum gates.

A Comparative Analysis of Performance of Shared Memory Cluster Computing Interconnection Systems

In recent past, many types of shared memory cluster computing interconnection systems have been proposed. Each of these systems has its own advantages and limitations. With the increase in system size of the cluster interconnection systems, the comparative analysis of their various performance measures becomes quite inevitable. The cluster architecture, load balancing, and fault tolerance are some of the important aspects, which need to be addressed. The comparison needs to be made in order to choose the best one for a particular application. In this paper, a detailed comparative study on four important and different classes of shared memory cluster architectures has been made. The systems taken up for the purpose of the study are shared memory clusters, hierarchical shared memory clusters, distributed shared memory clusters, and the virtual distributed shared memory clusters. These clusters are analyzed and compared on the basis of the architecture, load balancing, and fault tolerance aspects. The results of comparison are reported.

Survey on Fault-Tolerant Vehicle Design

Fault-tolerant vehicle design is an emerging inter-disciplinary research domain, which is of increased importance due to the electrification of automotive systems. The goal of fault-tolerant systems is to handle occuring faults under operational condition and enable the driver to get to a safe stop. This paper presents results from an extended survey on fault-tolerant vehicle design. It aims to provide a holistic view on the fault-tolerant aspects of a vehicular system. An overview of fault-tolerant systems in general and their design premises is given as well as the specific aspects related to automotive applications. The paper highlights recent and prospective development of vehicle motion control with integrated chassis control and passive and active fault-tolerant control. Also, fault detection and diagnosis methods are briefly described. The shift on control level of vehicles will be accompanied by basic structural changes within the network architecture. Control architecture as well as communication protocols and topologies are adapted to comply with the electrified automotive systems. Finally, the role of regulations and international standardization to enable fault-tolerant vehicle design is taken into consideration.

Logical Bell inequalities

Bell inequalities play a central role in the study of quantum non-locality and entanglement, with many applications in quantum information. Despite the huge literature on Bell inequalities, it is not easy to find a clear conceptual answer to what a Bell inequality is, or a clear guiding principle as to how they may be derived. In this paper, we introduce a notion of logical Bell inequality which can be used to systematically derive testable inequalities for a very wide variety of situations. There is a single clear conceptual principle, based on purely logical consistency conditions, which underlies our notion of logical Bell inequalities. We show that in a precise sense, all Bell inequalities can be taken to be of this form. Our approach is very general. It applies directly to any family of sets of commuting observables. Thus it covers not only the n-partite scenarios to which Bell inequalities are standardly applied, but also Kochen-Specker configurations, and many other examples. There is much current work on experimental tests for contextuality. Our approach directly yields, in a systematic fashion, testable inequalities for a very general notion of contextuality. There has been much work on obtaining proofs of Bell's theorem `without inequalities' or `without probabilities'. These proofs are seen as being in a sense more definitive and logically robust than the inequality-based proofs. On the hand, they lack the fault-tolerant aspect of inequalities. Our approach reconciles these aspects, and in fact shows how the logical robustness can be converted into systematic, general derivations of inequalities with provable violations. Moreover, the kind of strong non-locality or contextuality exhibited by the GHZ argument or by Kochen-Specker configurations can be shown to lead to maximal violations of the corresponding logical Bell inequalities.

Convergence analysis of evolutionary algorithms in the presence of crash-faults and cheaters

This paper analyzes the fault-tolerance nature of Evolutionary Algorithms (EAs) when executed in a distributed environment subjected to malicious acts. More precisely, the inherent resilience of EAs against two types of failures is considered: (1) crash faults, typically due to resource volatility which lead to data loss and part of the computation loss; (2) cheating faults, a far more complex kind of fault that can be modeled as the alteration of output values produced by some or all tasks of the program being executed. This last type of failure is due to the presence of cheaters on the computing platform. Most often in Global Computing (GC) systems such as BOINC, cheaters are attracted by the various incentives provided to stimulate the volunteers to share their computing resources: cheaters typically seek to obtain rewards with little or no contribution to the system. In this paper, the Algorithm-Based Fault Tolerance (ABFT) aspects of EAs against the above types of faults is characterized. Whereas the inherent resilience of EAs has been previously observed in the literature, for the first time, a formal analysis of the impact of the considered faults over the executed EA including a proof of convergence is proposed in this article.By the variety of problems addressed by EAs, this study will hopefully promote their usage in the future developments around distributed computing platform such as Desktop Grids and Volunteer Computing Systems or Cloud systems where the resources cannot be fully trusted.