Fault Tolerance Requirements Research Articles

Fault-tolerant feedback virtual machine deployment based on user-personalized requirements

A key requirement of the cloud platform is the reasonable deployment of its large-scale virtual machine infrastructure. The mapping relation between the virtual node and the physical node determines the specific resource distribution strategy and reliability of the virtual machine deployment. Resource distribution strategy has an important effect on performance, energy consumption, and guarantee of the quality of service of the computer, and serves an important role in the deployment of the virtual machine. To solve the problem of meeting the fault-tolerance requirement and guarantee high reliability of the application system based on the full use of the cloud resource under the prerequisite of various demands, the deployment framework of the feedback virtual machine in cloud platform facing the individual user’s demands of fault-tolerance level and the corresponding deployment algorithm of the virtual machine are proposed in this paper. Resource distribution strategy can deploy the virtual machine in the physical nodes where the resource is mutually complementary according to the users’ different requirements on virtual resources. The deployment framework of the virtual machine in this paper can provide a reliable computer configuration according to the specific fault-tolerance requirements of the user while considering the usage rate of the physical resources of the cloud platform. The experimental result shows that the method proposed in this paper can provide flexible and reliable select permission of fault-tolerance level to the user in the virtual machine deployment process, provide a pertinent individual fault-tolerant deployment method of the virtual machine to the user, and guarantee to meet the user service in a large probability to some extent.

The Fault-Tolerant Generator for Vehicles with a Hybrid Power Plant Design and Optimization

The aim of this work is the development of the algorithm and the permanent magnets starter-generator topology selecting process for a 500-kW hybrid power plant with a rotor speed of 2500 rpm, taking into account the fault-tolerance requirements for maximum energy density and maximum efficiency. The novelty of the algorithm is that numerical optimization is performed for each topology by using a genetic algorithm before the estimation of its main advantages. Thus, the optimal geometric dimensions of topologies are first determined and then compared. This feature distinguishes the proposed algorithm from those known from literature. The algorithm improves accuracy and provides an effective selection of starter-generator topologies for the transport industry. The topology selection is based on the methods of two-dimensional and three-dimensional computer simulations in the Ansys Maxwell software package. The 3D-simulation is used to estimate the distribution of eddy-current losses in the rotor. The obtained results are useful to those engineers and researchers who are engaged in the development of electrical machines for hybrid power plants.

Fault tolerant storage and data access optimization in data center networks

Data center, of which performance affects the cloud computing, is the key part of cloud computing technology. As cloud computing has penetrated into our daily life, the data stored in data center have increased rapidly, which increases the requirements of fault tolerance of distributed storage system. In the meantime, the efficiency of data access should be considered when applying network coding scheme in data center networks. This paper tackles these two issues. The first part of this paper proposes a fault-tolerant storage based placement strategy. We consider three factors: the efficiency of data access, the load of storage node, and the expectations of recovery time of failure nodes. When the loads of nodes are balance and recovery time for failure nodes is shorter, we can achieve a high fault-tolerance storage in data center networks. Simulation results show that the fault-tolerant placement has low expectation of recovery time and can achieve load balance. In the second part of this paper, we design a priority-queue based scheduling policy of data access to improve the efficiency of data access when deploying network coding in data center networks. Simulation results show that the proposed priority queue scheduling policy can achieve low delay by reducing the number of frozen servers.

Byzantine fault-tolerant and semantic-driven consensus protocol

To provide fault tolerance, modern distributed storage systems use specialized network topologies and consensus protocols that create high overheads. The main disadvantage of existing specialized topologies is a difficulty to implement an efficient data placement that takes into account locality of the data. In scientific problems very often it is necessary to provide the semantic proximity of the data at the nodes of the distributed system. Core drawback of modern consensus protocols is that most of them use messaging through broadcasting, which is impossible for large amounts of data and storage nodes. With more stringent requirements for a fault tolerance, e.g. requirement for resistance to Byzantine errors [1], ensuring of data localization becomes nearly impossible. The purpose of this paper is to implement a distributed consensus protocol that preserves data localization and is resistant to Byzantine errors. Theoretical tasks: a) consider how to implement distributed services based on finite state machines; b) consider how to ensure Byzantine fault tolerance; c) consider methods for organizing the semantic proximity of data. Practical tasks: a) develop ways to jointly ensure the Byzantine fault tolerance and locality of data; b) study the shortcomings of the joint provision of Byzantine fault tolerance and locality of data; c) develop a protocol of Byzantine consensus using semantic links between data; d) analyze the performance of the developed protocol within the framework of applied tasks. The object of the study is a distributed data storage system with the requirement for Byzantine fault tolerance. The subject of this study is the provision of Byzantine fault tolerance in conjunction with the use of semantic links between the data. The subject of this study has never been the subject of a special scientific study. Separate scientific foundations of this problematic set in the present study were developed in separate works on Byzantine fault tolerance, local hash methods and dimensional reduction.

Development of software monitoring module for multi-angle electric impedance tomography method research

This paper describes the experience of software development for multi-angle electrical impedance tomography. The relevance and necessity of an architecture for this kind of software product creating is considered, requirements for reliability and fault tolerance are defined. The choice of the architectural model has been made, design patterns have also been chosen taking into account the prospective scenario of using the developed software, their advantages are shown too. The most important attributes of software quality are described, which should implement the developed software product. The considered attributes of quality are projected on specific modules of the developed software. The architectural models and templates chosen during design are described, their advantages and disadvantages are considered. Support issues for the software developed by the cross-platform are discussed, and the possibility of working in various operating systems is demonstrated.

WCET-Aware Control Flow Checking With Super-Nodes for Resource-Constrained Embedded Systems

Safety-critical embedded systems in application domains, such as aerospace, automotive, and industrial automation, must satisfy dual requirements of fault-tolerance and real-time predictability. Control flow checking is an effective technique for improving embedded systems’ reliability by online monitoring and checking of software control flow to detect runtime deviations from the control flow graph. However, inserting instrumentation code in every basic block incurs significant execution time overhead, which may cause the program to violate its timing constraints. In this paper, we propose to selectively instrument a subset of code regions that are larger than basic blocks, called super-nodes, in order to make the program partially resilient to control flow errors while keeping the program worst-case execution time (WCET) below a given upper bound. WCET analysis is invoked to estimate the program WCET and to identify the corresponding worst-case execution path (WCEP). An ILP formulation is used to judiciously select a subset of super-nodes on the WCEP for instrumentation, so that the best fault detection coverage is achieved without violating the given WCET upper bound. The optimization is repeated for each identified WCEP until the program WCET satisfies the WCET upper bound. Experimental results demonstrate significant improvements of fault detection coverage compared with related work.

Fault-Tolerant Scheduling for Hybrid Real-Time Tasks Based on CPB Model in Cloud

Clouds are becoming a very important platform for hybrid real-time tasks. To enhance the reliability of cloud, fault tolerance of cloud becomes a critical issue. However, the complexities and specialties of traditional fault-tolerant mechanisms cannot meet the fault-tolerant requirements of clouds. To address this issue, we propose a novel fault-tolerant scheduling algorithm named ARCHER for hybrid tasks in cloud. ARCHER has three significant characteristics: 1) it integrates the traditional primary/backup model and checkpoint technology which can flexibly determine the execution time of the backup copies of tasks, so it greatly enhances the resource utilization and produces more time slots to execute tasks as many as possible; 2) it employs task classification mechanism to realize precise scheduling for different types of tasks and virtual machines, which reduces the response time of clouds; and 3) it uses time slot exploiting mechanism, task forward mechanism, and task transform mechanism to achieve high-resource utilization. We conduct extensive simulations to evaluate the performance of ARCHER by comparing it with four baseline algorithms. The experimental results show that ARCHER can effectively improve the resource utilization of cloud while guaranteeing fault tolerance.

A Comprehensive Reliability Assessment of Fault-Resilient Network-on-Chip Using Analytical Model

The component’s failure in network-on-chips (NoCs) has been a critical factor on the system’s reliability. In order to alleviate the impact of faults, fault tolerance has been investigated in the recent years to enhance NoC’s robustness. Due to the vast selection of fault-tolerance mechanisms and critical design constraints, selecting and configuring an appropriate mechanism to satisfy the fault-tolerance requirements constitute new challenges for designers. Consequently, reliability assessment has become prominent for the early stages of manufacturing process to solve these problems. This paper approaches the fault-tolerance analysis by providing an analytical model to approximate the lifetime reliability and compares it with a system-level simulation. Based on the proposed approach, we measure the fault-tolerance efficiency using a new parameter, named reliability acceleration factor. The goal of this paper is to provide an efficient and accurate reliability assessment to help designers easily understand and evaluate the advantages and drawbacks of their potential fault-tolerance methods.

A Stream-Oriented Real-Time Fault Tolerant Strategy for Monitoring Big Data of Power Distribution Network Based on Spark

Aiming at the existing problem of monitoring data volume blowout and lack of valid real-time distributed fault tolerant strategy in power distribution network, a new fault tolerant strategy based on Spark micro batch computing model is proposed. Depending on the design technique of resilient distributed data set renewal and lineage mechanism, the lineage chain retrospection in fault tolerance of distributed data is realized. This strategy can meet the real-time fault tolerant performance requirements of monitoring big data, and it is of evident practical value for improving the fault tolerant performance of dispatching system in intelligent power distribution network.

Impact of a multi-star winding on the reliability of a permanent magnet generator for marine current turbine

For Marine current turbine (MCT), low speed Surface-mounted Permanent Magnet generator is a solution to satisfy the efficiency and fault tolerant requirements. This is supposed to be true if the winding is made with several non-shifted three-phase stars that could be supplied with standard modular voltage source inverters. This paper investigates the impact of the star number on the MCT energy yield if the system is conceived to operate with disconnected inverters. For this purpose, a method to calculate the extracted power according to the tidal speed for a given star number and a given activated star number is detailed. A rainflow counting method is used to account the stress due to the tidal speed change on the star converter: the impact of the star number on the resilience capability of the MCT is then quantified. By assuming a ten-year period without converter repair, according to the introduced probabilistic approach, the star number increase improves the reliability and three-star configuration appears as a trade-off.

A sensor-service collaboration approach for target tracking in wireless camera networks

Mobile target tracking is a necessary function of some emerging application domains, such as virtual reality, smart home and intelligent healthcare. However, existing portable devices for target tracking are resource intensive and high-cost. Camera tracking is an effective location tracking way for those emerging applications which can reuse the existing ubiquitous video monitoring system. This paper proposes a dynamic community-based camera collaboration (D3C) framework for target location and tracking. The contributions of D3C mainly include that (1) nonlinear perspective projection model is selected as the camera sensing model and sequential Monte Carlo is employed to predict the target location; (2) a dynamic collaboration scheme is proposed, it is based on the local community-detection theory deriving from social network analysis. The performance of proposed approach is validated by both synthetic datasets and real-world application. The experiment results show that D3C meets the versatility, real-time and fault tolerance requirements of target tracking applications.

Network configuration synthesis with abstract topologies

We develop Propane/AT, a system to synthesize provably-correct BGP (border gateway protocol) configurations for large, evolving networks from high-level specifications of topology, routing policy, and fault-tolerance requirements. Propane/AT is based on new abstractions for capturing parameterized network topologies and their evolution, and algorithms to analyze the impact of topology and routing policy on fault tolerance. Our algorithms operate entirely on abstract topologies. We prove that the properties established by our analyses hold for every concrete instantiation of the given abstract topology. Propane/AT also guarantees that only incremental changes to existing device configurations are required when the network evolves to add or remove devices and links. Our experiments with real-world topologies and policies show that our abstractions and algorithms are effective, and that, for large networks, Propane/AT synthesizes configurations two orders of magnitude faster than systems that operate on concrete topologies.

Finite state machine‐based fault tolerance technique with enhanced area and power of synthesised sequential circuits

Recently, a finite state machine-based fault tolerance technique for sequential circuits based on protecting few states with high probability of occurrence has been proposed. In this study, the authors propose an algorithm that starts with a given state assignment targeting the optimisation of either area or power and generates a state assignment that preserves the original state assignment and satisfies the fault tolerance requirements for the protected states. Experimental results demonstrate the effectiveness of the proposed algorithm in significantly reducing the area and power of synthesised sequential circuits while enhancing their fault tolerance.

Crossed Cube Ring: A k-connected virtual backbone for wireless sensor networks

Connected dominating set is widely used to construct a virtual backbone for effective routing in wireless sensor networks. The k-connected dominating set, where at least k disjoint paths between any pair of nodes exist, is used to meet the fault tolerance requirement of wireless sensor networks. It is an open problem of finding a minimum approximation ratio, measured by the ratio between the number of nodes in the constructed virtual backbone and the number of nodes in the optimal minimum connected dominating set. In this paper, we propose Crossed Cube Ring Algorithm (CCRA) to make the k-connected dominating set virtual backbone with a lower approximation ratio than any existing algorithms. Both theoretical analysis and simulation experiments demonstrate that CCRA can reduce the approximation ratio by 20% than any other algorithms. Therefore, CCRA can be used to construct more compact k-connected dominating set than the conventional algorithms.

Toward Human-Scale Brain Computing Using 3D Wafer Scale Integration

The Von Neumann architecture, defined by strict and hierarchical separation of memory and processor, has been a hallmark of conventional computer design since the 1940s. It is becoming increasingly unsuitable for cognitive applications, which require massive parallel processing of highly interdependent data. Inspired by the brain, we propose a significantly different architecture characterized by a large number of highly interconnected simple processors intertwined with very large amounts of low-latency memory. We contend that this memory-centric architecture can be realized using 3D wafer scale integration for which the technology is nearing readiness, combined with current CMOS device technologies. The natural fault tolerance and lower power requirements of neuromorphic processing make 3D wafer stacking particularly attractive. In order to assess the performance of this architecture, we propose a specific embodiment of a neuronal system using 3D wafer scale integration; formulate a simple model of brain connectivity including short- and long-range connections; and estimate the memory, bandwidth, latency, and power requirements of the system using the connectivity model. We find that 3D wafer scale integration, combined with technologies nearing readiness, offers the potential for scaleup to a primate-scale brain, while further scaleup to a human-scale brain would require significant additional innovations.

Fault-Tolerant Preemptive Aperiodic RT Scheduling by Supervisory Control of TDES on Multiprocessors

Safety-critical real-time systems must meet stringent timing and fault-tolerance requirements. This article proposes a methodology for synthesizing an optimal preemptive multiprocessor aperiodic task scheduler using a formal supervisory control framework. The scheduler can tolerate single/multiple permanent processor faults. Further, the synthesis framework has been empowered with a novel BDD-based symbolic computation mechanism to control the exponential state-space complexity of the optimal exhaustive enumeration-oriented synthesis methodology.

Measuring performance of middleware technologies for medical systems

After decades of design, development and usage of distributed application technologies, there are numerous communication middleware architectures and implementations in the market that have reached a considerable maturity level. A large number of them are open source initiatives that have shown efficiency and good performance in a broad range of domains, from banking to gaming. These are low cost solutions, easily programmable and of high interest to be explored in areas such as cyber-physical medical systems that have special requirements for safety, availability, communication latency, real-time operation, and fault tolerance. This paper analyzes the suitability of two open source communication middleware technologies, Ice (Internet Communication Engine) and AMQP (Advanced Message Queuing Protocol), as software elements suitable for developing audio transmission and reception systems for low cost medical applications. The paper simulates an audio application with both technologies, made of a server (nurse central) that receives and processes audio media from several clients (patients); communication can be triggered concurrent from multiple patients and in both directions. Stress tests with high load conditions are simulated in the experiments to show the behavior of both technologies mainly with respect to their stability and overhead.

QoT-aware elastic bandwidth allocation and spare capacity assignment in flexible island-based optical transport networks under shared risk link group constraints

This paper focuses on the problem of provisioning multi-granularity static lightpath connections with fault-tolerant requirements in survivable island-based translucent optical networks with traffic grooming capabilities. The problem is tackled for the first time, to the best of our knowledge, taking into account both Quality of Transmission (QoT) and Shared Risk Link Group (SRLG) constraints. A two phase heuristic algorithm is proposed relying on a novel generic purpose-built auxiliary graph model that may support various factors of network heterogeneity (i.e., network nodes with different wavelength-conversion, regeneration and traffic grooming capabilities), and represent numerous network constraints related mainly to QoT requirements and network-resources. The purpose of the proposed heuristic is to optimize the utilisation of the available network resources and hence the network throughput through the simultaneous use of traffic grooming and two resource sharing techniques namely the Generalized Backup-Backup multiplexing (GBBM) and the Generalized Adaptive Primary-Backup Multiplexing (GAPBM) which are combined for the first time, as far as we know, under a static traffic scenario, and performed in such a way that 100% QoT-aware SRLG-fault recoverability is still guaranteed for all serviced lightpath requests. The performances of the proposed solution are demonstrated through multiple simulation experiments conducted on different network topologies.

FICTC: fault-tolerance-and-interference-aware topology control for wireless multi-hop networks

K-connectivity-based topology control can improve fault-tolerant performance of multi-hop wireless networks. Existing algorithms mainly focused on preserving the same k-connectivity between any two nodes. However, in practical network deployments, the algorithms enforcing k-connectivity degrade network performance, when the topology requires heterogeneous nodal fault-tolerant requirements. In this paper, we aim to develop interference-aware topology control based on the different k ij connectivities between any two nodes and propose a fault-tolerance-and-interference-aware topology control (FICTC) algorithm. It can be proved that FICTC can meet different fault-tolerant requirements between any two nodes, and is the optimum solution for min-max network interference. Simulation results show that FICTC not only leads to weaker interference, but also achieves higher throughput and lower end-to-end (E2E) delay than existing fault-tolerant topology control schemes.

RelaxFault memory repair

Memory system reliability is a serious concern in many systems today, and is becoming more worrisome as technology scales and system size grows. Stronger fault tolerance capability is therefore desirable, but often comes at high cost. In this paper, we propose a low-cost, fault-aware, hardware-only resilience mechanism, RelaxFault , that repairs the vast majority of memory faults using a small amount of the LLC to remap faulty memory locations. RelaxFault requires less than 100KiB of LLC capacity, has near-zero impact on performance and power. By repairing faults, RelaxFault relaxes the requirement for high fault tolerance of other mechanisms, such as ECC. A better tradeoff between resilience and overhead is made by exploiting an understanding of memory system architecture and fault characteristics. We show that RelaxFault provides better repair capability than prior work of similar cost, improves memory reliability to a greater extent, and significantly reduces the number of maintenance events and memory module replacements. We also propose a more refined memory fault model than prior work and demonstrate its importance.