Fault Tolerance Measures Research Articles

Generalized measures of fault tolerance in exchanged hypercubes

The exchanged hypercube EH(s,t), proposed by Loh et al. [P.K.K. Loh, W.J. Hsu, Y. Pan, The exchanged hypercube, IEEE Transactions on Parallel and Distributed Systems 16 (9) (2005) 866–874], is obtained by removing edges from a hypercube Qs+t+1. This paper considers a kind of generalized measures κ(h) and λ(h) of fault tolerance in EH(s,t) with 1≤s≤t and determines κ(h)(EH(s,t))=λ(h)(EH(s,t))=2h(s+1−h) for any h with 0≤h≤s. The results show that at least 2h(s+1−h) vertices (resp. 2h(s+1−h) edges) of EH(s,t) have to be removed to get a disconnected graph that contains no vertices of degree less than h, and generalizes some known results.

Combining decomposition and reduction for state space analysis of a self-stabilizing system

Fault tolerance measures of distributed systems can be calculated precisely by state space analysis of the Markov chain corresponding to the product of the system components. The power of such an approach is inherently confined by the state space explosion, i.e. the exponential growth of the Markov chain in the size of the underlying system. We propose a decompositional method to alleviate this limitation. Lumping is a well-known reduction technique facilitating computation of the relevant measures on the quotient of the Markov chain under lumping equivalence. In order to avoid computation of lumping equivalences on intractably large Markov chains, we propose a system decomposition supporting local lumping on the considerably smaller Markov chains of the subsystems. Recomposing the lumped Markov chains of the subsystems constructs a lumped transition model of the whole system, thus avoiding the construction of the full product chain. An example demonstrates how the limiting window availability (i.e. a particular fault tolerance measure) can be computed for a self-stabilizing system exploiting lumping and decomposition.

Multi-sensor fault tolerant measurement based on Tagaki–Sugeno fuzzy model

A multiple fault tolerant measurement system based on nonlinear dynamic models, special searching algorithm, principle components decomposition and Q test is developed. The proposed system uses a model-based estimator to deliver symptoms. The symptoms are then analyzed in a statistical unit in order to detect the faults and isolate the faulty sensors. Multi-layer perceptron networks, radial basis function networks and Tagaki–Sugeno fuzzy models were examined for the fault estimator module and among these fuzzy models presented the best performance. The main advantages of the proposed scheme are the capability to detect, isolate and repair multiple faults in both input and output sensors and the feasibility to be applied to any system with as many sensors as required, all due to particular design of its model-based estimator. The system was tested on a CSTH model developed based on an experimental platform; different experiments demonstrated satisfactory results.

Fault tolerance of augmented cubes

The augmented cube AQn, proposed by Choudum and Sunitha [S.A. Choudum, V. Sunitha, Augmented cubes, Networks 40 (2) (2002) 71-84], is a (2n - 1)-regular (2n - 1)-connected graph (n ≥ 4). This paper determines that the 2-extra connectivity of AQn is 6n - 17 for n ≥ 9 and the 2-extra edge-connectivity is 6n - 9 for n ≥ 4. That is, for n ≥ 9 (respectively, n ≥ 4), at least 6n - 17 vertices (respectively, 6n - 9 edges) of AQn have to be removed to get a disconnected graph that contains no isolated vertices and isolated edges. When the augmented cube is used to model the topological structure of a large-scale parallel processing system, these results can provide more accurate measurements for reliability and fault tolerance of the system.

AN EFFICIENT FAULT TOLERANT SCHEDULING APPROACH FOR COMPUTATIONAL GRID

Grid computing serves as an important technology to facilitate distributed computation computational grids solve large scale scientific problems using heterogeneous geographically distributed resources. Problems like dispatching and scheduling of tasks are considered as major issues in computational grid environment. The Grid Scheduler must select proper resources for executing the tasks with less response time. There are various reasons such as network failure, overloaded resource conditions, or non-availability of required software components for execution failure. Thus, fault-tolerant systems should be able to identify and handle failures and support reliable execution in the presence of failures. Hence the integration of fault tolerance measures and communication time with scheduling gains much importance. In this study, a new fault tolerance based scheduling approach Fault Tolerant Min-Min (FTMM) for scheduling statically available meta tasks is proposed wherein failure rate and the fitness value are calculated. The performance of the fault tolerant scheduling policy is compared with min-min scheduling policy using GridSim and the results shows that the proposed policy performs better with less makespan in the presence of failures. The number of tasks successfully completed is also more when compared to the non-fault tolerant min-min scheduling policy. Thus the proposed FTMM algorithm not only achieves better hit rate but also improved makespan.

The Study on Software Fault Tolerance

Software Fault -tolerance is an effective and reliable design technique and Recovery Block Scheme is an important Software Fault-tolerant measure. Here is the brief introduction of the implementation of Software Fault-tolerant technique and the design pattern by employing software redundancy and then proposes the implementation of Recovery Block Scheme. Firstly, based on the program block’s fault captured by exception-progressing mechanism, it applies the Command Pattern and Active Objective Pattern to manage and schedule arithmetic unit to achieve rollback, clears the data generated by fault operation block and restores to the state before the operation. The design pattern provides a widely available recovery block schemes design pattern, simplifies the implementation of arithmetic unit and gives the core algorithm through Java.

Adaptively fault-tolerant topology control algorithm for wireless sensor networks

Fault tolerance is one of the critical characteristic of wireless sensor networks (WSNs). The most of researches on fault-tolerant topologies are concentrated on graphics structure properties. However, some attributes of sensor nodes neglected have the same decisive role in topology tolerance. In this paper, by analyzing effects of node attributes on topology tolerance, we presented a new fault-tolerant measurement index, fault-tolerant degree. Then an adaptively fault-tolerant topology control algorithm was proposed to allocate networks resources reasonably. In the algorithm, nodes with higher fault-tolerant degree are selected as backbone nodes, and each backbone node has the backup nodes for promoting performances of networks, including energy efficiency and fault-tolerant capability. Theoretical analysis and simulation results show that the algorithm is efficient and reliable to construct and maintain the fault-tolerant topology for networks.

Generalized Measures of Edge Fault Tolerance in (n,k)-star Graphs

This paper considers a kind of generalized measure of fault tolerance in the -star graph for and , and determines , which implies that at least edges of have to remove to get a disconnected graph that contains no vertices of degree less than . This result shows that the -star graph is robust when it is used to model the topological structure of a large-scale parallel processing system.

Containers and wide diameters of $P_3(G)$

The $P_3$ intersection graph of a graph $G$ has for vertices all the induced paths of order 3 in $G$. Two vertices in $P_3(G)$ are adjacent if the corresponding paths in $G$ are not disjoint. A $w$-container between two different vertices $u$ and $v$ in a graph $G$ is a set of $w$ internally vertex disjoint paths between $u$ and $v$. The length of a container is the length of the longest path in it. The $w$-wide diameter of $G$ is the minimum number $l$ such that there is a $w$-container of length at most $l$ between any pair of different vertices $u$ and $v$ in $G$. Interconnection networks are usually modeled by graphs. The $w$-wide diameter provides a measure of the maximum communication delay between any two nodes when up to $w-1$ nodes fail. Therefore, the wide diameter constitutes a measure of network fault tolerance. In this paper we construct containers in $P_3 (G)$ and apply the results obtained to the study of their connectivity and wide diameters.

Generalized measures of fault tolerance in hypercube networks

A vertex subset F is an R g -cut of a connected graph G if G − F is disconnected and every vertex in G − F has at least g fault-free neighbors in G − F . The cardinality of the minimum R g -cut of G is the R g -connectivity of G , denoted by κ g ( G ) . This parameter measures a kind of conditional fault tolerance of networks. In this work, we characterize the smallest components after deleting a minimum R g -cut of hypercubes. Our work strengthens the results of [A.H. Esfahanian, Generalized measure of fault tolerance with application to N -cube networks, IEEE Trans. Comput. 38 (1989) 1586–1591] and [S. Latifi, M. Hegde, M. Naraghi-Pour, Conditional connectivity measures for large multiprocessor systems, IEEE Trans. Comput. 43 (1994) 218–222] and also corrects bugs in them.

Fault tolerant measurement system based on Takagi–Sugeno fuzzy models for a gas turbine in a combined cycle power plant

A fault tolerant measurement system for a gas turbine in a combined cycle power plant, based on dynamic models, principal component analysis (PCA) and Q test, is presented. The proposed scheme makes use of a model-based symptom generator, which delivers fault signals obtained by using direct identification of parity relations and structured residuals. Symptoms are then analyzed in a statistical module achieving fault diagnosis and reconstruction of the faulty signals. The scheme presents as main advantage the ability of detecting faults in both input and output sensors due to its particular structure. Tests carried out on the gas turbine of the San Isidro combined cycle power plant in the V Region, Chile, show that Takagi–Sugeno fuzzy models present the best fitting performance and an acceptable computational cost in comparison with autoregressive exogenous, state space, and neural models. Real time software based on this scheme has been developed and connected to Osisoft PI System ™ . The software is running at Endesa Monitoring and Diagnosis Center in Santiago, Chile.

Dealing with Transient Faults in the Interconnection Network of CMPs at the Cache Coherence Level

The importance of transient faults is predicted to grow due to current technology trends of increased scale of integration. One of the components that will be significantly affected by transient faults is the interconnection network of chip multiprocessors (CMPs). To deal efficiently with these faults and differently from other authors, we propose to use fault-tolerant cache coherence protocols that ensure the correct execution of programs when not all messages are correctly delivered. We describe the extensions made to a directory-based cache coherence protocol to provide fault tolerance and provide a modified set of token counting rules which are useful to design fault-tolerant token-based cache coherence protocols. We compare the directory-based fault-tolerant protocol with a token-based fault-tolerant one. We also show how to adjust the fault tolerance parameters to achieve the desired level of fault tolerance and measure the overhead achieved to be able to support very high fault rates. Simulation results using a set of scientific, multimedia, and commercial applications show that the fault tolerance measures have virtually no impact on execution time with respect to a non-fault-tolerant protocol. Additionally, our protocols can support very high rates of transient faults at the cost of slightly increased network traffic.

Distributed error confinement

We study error confinement in distributed applications, which can be viewed as an extreme case of various fault locality notions studied in the past. Error confinement means that to the external observer, only nodes that were directly hit by a fault may deviate from their specified correct behavior, and only temporarily. The externally observable behavior of all other nodes must remain impeccable, even though their internal state may be affected. Error confinement is impossible if an adversary is allowed to inflict arbitrary transient faults on the system, since the faults might completely wipe out input values. We introduce a new fault-tolerance measure we call agility , which quantifies the fault tolerance of an algorithm that disseminates information against state corrupting faults. We then propose broadcast algorithms that guarantee error confinement with optimal agility to within a constant factor in synchronous networks. These algorithms can serve as building blocks in more general reactive systems. Previous results in exploring locality in reactive systems were not error confined, or allowed a wide range of behaviors to be considered correct. Our results also include a new technique that can be used to analyze the “cow path” problem.

서비스로봇의 신뢰성 향상을 위한 OPRoS 기반 Fault-tolerance 기법

For commercial success of emerging service robots, the fault tolerant technology for system reliability and human safety is crucial. Traditionally fault tolerance methods have been implemented in application level. However, from our studies on the common design patterns in fault tolerance, we argue that a framework-based approach provides many benefits in providing reliability for system development. To demonstrate the benefits, we build a framework-based fault tolerant engine for OPRoS (Open Platform for Robotic Services) standards. The fault manager in framework provides a set of fault tolerant measures of detection, isolation, and recovery. The system integrators choose the appropriate fault handling tools by declaring XML configuration descriptors, considering the constraints of components and operating environment. By building a fault tolerant navigation application from the non-faulttolerant components, we demonstrate the usability and benefits of the proposed framework-based approach.

Restricted power domination and fault-tolerant power domination on grids

The power domination problem is to find a minimum placement of phase measurement units (PMUs) for observing the whole electric power system, which is closely related to the classical domination problem in graphs. For a graph G = ( V , E ) , the power domination number of G is the minimum cardinality of a set S ⊆ V such that PMUs placed on every vertex of S results in all of V being observed. A vertex with a PMU observes itself and all its neighbors, and if an observed vertex with degree d > 1 has only one unobserved neighbor, then the unobserved neighbor becomes observed. Although the power domination problem has been proved to be NP-complete even when restricted to some special classes of graphs, Dorfling and Henning in [M. Dorfling, M.A. Henning, A note on power domination in grid graphs, Discrete Applied Mathematics 154 (2006) 1023–1027] showed that it is easy to determine the power domination number of an n × m grid. Their proof provides an algorithm for giving a minimum placement of PMUs. In this paper, we consider the situation in which PMUs may only be placed within a restricted subset of V . Then, we present algorithms to solve this restricted type of power domination on grids under the conditions that consecutive rows or columns form a forbidden zone. Moreover, we also deal with the fault-tolerant measurement placement in the designed scheme and provide approximation algorithms when the number of faulty PMUs does not exceed 3.

Conditional diagnosability of alternating group networks

The growing size of a multiprocessor system increases its vulnerability to component failures. In order to maintain the system's high reliability, it is crucial to identify and replace the faulty processors through testing, a process known as fault diagnosis. The minimum size of a largest connected component in such a networked system is typically used as a measure for fault tolerance of the system. For this measure, the conditional diagnosability of the system in terms of an alternating group network is important, which is studied in the present paper under a comparison model, with some precise and useful bounds of tolerance derived.

Fault tolerance measures for large-scale wireless sensor networks

Connectivity , primarily a graph-theoretic concept, helps define the fault tolerance of wireless sensor networks (WSNs) in the sense that it enables the sensors to communicate with each other so their sensed data can reach the sink. On the other hand, sensing coverage , an intrinsic architectural feature of WSNs plays an important role in meeting application-specific requirements, for example, to reliably extract relevant data about a sensed field. Sensing coverage and network connectivity are not quite orthogonal concepts. In fact, it has been proven that connectivity strongly depends on coverage and hence considerable attention has been paid to establish tighter connection between them although only loose lower bound on network connectivity of WSNs is known. In this article, we investigate connectivity based on the degree of sensing coverage by studying k-covered WSNs, where every location in the field is simultaneously covered (or sensed) by at least k sensors (property known as k-coverage , where k is the degree of coverage ). We observe that to derive network connectivity of k -covered WSNs, it is necessary to compute the sensor spatial density required to guarantee k -coverage. More precisely, we propose to use a model, called the Reuleaux Triangle , to characterize k -coverage with the help of Helly's Theorem and the analysis of the intersection of sensing disks of k sensors. Using a deterministic approach, we show that the sensor spatial density to guarantee k -coverage of a convex field is proportional to k and inversely proportional to the sensing range of the sensors. We also prove that network connectivity of k -covered WSNs is higher than their sensing coverage k . Furthermore, we propose a new measure of fault tolerance for k -covered WSNs, called conditional fault tolerance , based on the concepts of conditional connectivity and forbidden faulty sensor set that includes all the neighbors of a given sensor. We prove that k -covered WSNs can sustain a large number of sensor failures provided that the faulty sensor set does not include a forbidden faulty sensor set.

Fault-Tolerant Indirect Adaptive Neurocontrol for a Static Synchronous Series Compensator in a Power Network With Missing Sensor Measurements

Identification and control of nonlinear systems depend on the availability and quality of sensor measurements. Measurements can be corrupted or interrupted due to sensor failure, broken or bad connections, bad communication, or malfunction of some hardware or software (referred to as missing sensor measurements in this paper). This paper proposes a novel fault-tolerant indirect adaptive neurocontroller (FTIANC) for controlling a static synchronous series compensator (SSSC), which is connected to a power network. The FTIANC consists of a sensor evaluation and (missing sensor) restoration scheme (SERS), a radial basis function neuroidentifier (RBFNI), and a radial basis function neurocontroller (RBFNC). The SERS provides a set of fault-tolerant measurements to the RBFNI and RBFNC. The resulting FTIANC is able to provide fault-tolerant effective control to the SSSC when some crucial time-varying sensor measurements are not available. Simulation studies are carried out on a single machine infinite bus (SMIB) as well as on the IEEE 10-machine 39-bus power system, for the SSSC equipped with conventional PI controllers (CONVC) and the FTIANC without any missing sensors, as well as for the FTIANC with multiple missing sensors. Results show that the transient performances of the proposed FTIANC with and without missing sensors are both superior to the CONVC used by the SSSC (without any missing sensors) over a wide range of system operating conditions. The proposed fault-tolerant control is readily applicable to other plant models in power systems.

Design and Analysis of a Fault-Tolerant Coplanar Gyro-Free Inertial Measurement Unit

This paper presents a novel design of a fault-tolerant, coplanar, and gyro-free inertial measurement unit (IMU) that consists of 13 single-axis linear accelerometers and can perform six degree-of-freedom (DOF) measurements for an object in motion. This design uses a combination of redundant accelerometers, an innovative real-time fault-identification technique, together with state-estimation techniques to facilitate robust six DOF measurements, even when some of its accelerometers produce faulty outputs. A design example indicates that the proposed fault-tolerant design and compensation algorithm can detect and correct the biased accelerometer outputs in real time. In this simulation example, the accelerometer measurement noise is assumed to be white and set at 0.1 m/s <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> . The minimum detectable dc-offset value is 0.1 m/s <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> , which is the same as the standard deviation of the accelerometer measurement noise. The compensated accelerometer outputs were used to construct an "observer-based" gyro-free IMU. The angular-velocity estimation accuracy is 4 X 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-3</sup> rad/s, and the linear-acceleration accuracy is less than 0.24 m/s <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> . The IMU output accuracy is not affected by the proposed fault-compensation algorithm.

Fault-Tolerant Optimal Neurocontrol for a Static Synchronous Series Compensator Connected to a Power Network

This paper proposes a fault-tolerant optimal neurocontrol scheme (FTONC) for a Static Synchronous Series Compensator (SSSC) connected to a multi-machine benchmark power system. The dual heuristic programming technique and the radial basis function neural networks are used to design a nonlinear optimal neurocontroller (NONC) for the external control of the SSSC. Compared to the conventional external linear controller, The NONC improves the damping performance of the SSSC. The internal control of the SSSC is achieved by a conventional liner controller. A sensor evaluation and (missing sensor) restoration scheme (SERS) is designed by using the auto-associative neural networks and the particle swarm optimization technique. This SERS provides a set of fault-tolerant measurements to the SSSC controllers and therefore guarantees a fault-tolerant control for the SSSC. The proposed FTONC is verified by simulation studies in PSCAD/EMTDC environment.