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Reliability, IEEE Transactions on

Issue 3 • Date Sept. 2005

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  • Table of contents

    Publication Year: 2005 , Page(s): c1 - 369
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  • IEEE Transactions on Reliability publication information

    Publication Year: 2005 , Page(s): c2
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  • A bibliography of accelerated test plans part II - references

    Publication Year: 2005 , Page(s): 370 - 373
    Cited by:  Papers (27)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (152 KB) |  | HTML iconHTML  

    This is the bibliography referenced in the article by Wayne B Nelson titled "A bibliography of accelerated test plans," published in the IEEE Transactions on Reliability June 2005 issue (vol.54, no.2, ISSN 0018-9529). View full abstract»

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  • Parameter estimation for a modified Weibull distribution, for progressively type-II censored samples

    Publication Year: 2005 , Page(s): 374 - 380
    Cited by:  Papers (19)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (712 KB) |  | HTML iconHTML  

    In this paper, the estimation of parameters based on a progressively Type-II censored sample from a modified Weibull distribution is studied. The likelihood equations, and the maximum likelihood estimators are derived. The estimators based on a least-squares fit of a multiple linear regression on a Weibull probability paper plot are compared with the MLE via Monte Carlo simulations. The observed Fisher information matrix, as well as the asymptotic variance-covariance matrix of the MLE are derived. Approximate confidence intervals for the parameters are constructed based on the s-normal approximation to the asymptotic distribution of MLE, and log-transformed MLE. The coverage probabilities of the individual s-normal-approximation confidence intervals for the parameters are examined numerically. Some recommendations are made from the results of a Monte Carlo simulation study, and a numerical example is presented to illustrate all of the methods of inference developed here. View full abstract»

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  • On the use of data compression measures to analyze robust designs

    Publication Year: 2005 , Page(s): 381 - 388
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (304 KB) |  | HTML iconHTML  

    In this paper, we suggest a potential use of data compression measures, such as the Entropy, and the Huffman Coding, to assess the effects of noise factors on the reliability of tested systems. In particular, we extend the Taguchi method for robust design by computing the entropy of the percent contribution values of the noise factors. The new measures are computed already at the parameter-design stage, and together with the traditional S/N ratios enable the specification of a robust design. Assuming that (some of) the noise factors should be naturalized, the entropy of a design reflects the potential efforts that will be required in the tolerance-design stage to reach a more reliable system. Using a small example, we illustrate the contribution of the new measure that might alter the designer decision in comparison with the traditional Taguchi method, and ultimately obtain a system with a lower quality loss. Assuming that the percent contribution values can reflect the probability of a noise factor to trigger a disturbance in the system response, a series of probabilistic algorithms can be applied to the robust design problem. We focus on the Huffman coding algorithm, and show how to implement this algorithm such that the designer obtains the minimal expected number of tests in order to find the disturbing noise factor. The entropy measure, in this case, provides the lower bound on the algorithm's performance. View full abstract»

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  • Robust weighted likelihood estimation of exponential parameters

    Publication Year: 2005 , Page(s): 389 - 395
    Cited by:  Papers (7)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (496 KB) |  | HTML iconHTML  

    The problem of estimating the parameter of an exponential distribution when a proportion of the observations are outliers is quite important to reliability applications. The method of weighted likelihood is applied to this problem, and a robust estimator of the exponential parameter is proposed. Interestingly, the proposed estimator is an α-trimmed mean type estimator. The large-sample robustness properties of the new estimator are examined. Further, a Monte Carlo simulation study is conducted showing that the proposed estimator is, under a wide range of contaminated exponential models, more efficient than the usual maximum likelihood estimator in the sense of having a smaller risk, a measure combining bias & variability. An application of the method to a data set on the failure times of throttles is presented. View full abstract»

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  • The NBUT class of life distributions

    Publication Year: 2005 , Page(s): 396 - 401
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (208 KB) |  | HTML iconHTML  

    A new class of life distributions, namely new better than used in the total time on test transform ordering (NBUT), is introduced. The relationship of this class to other classes of life distributions, and closure properties under some reliability operations, are discussed. We provide a simple argument based on stochastic orders that the family of the NBUT distribution class is closed under the formation of series systems in case of independent identically distributed components. Behavior of this class is developed in terms of the monotonicity of the residual life of k-out-of-n systems given the time at which the (n-k)-th failure has occurred. Finally, we discuss testing exponentially against the NBUT aging property. View full abstract»

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  • Optimal, and reliable communication in hypercubes using extended safety vectors

    Publication Year: 2005 , Page(s): 402 - 411
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (680 KB) |  | HTML iconHTML  

    We propose a new coding method of limited global fault information in an n-cube. First, each node collects precise fault information within distance-d, and then fault information about nodes that are more than distance-d away is coded in a special way. Specifically, in our approach, each node in a cube-based multicomputer of dimension n is associated with an extended safety vector of n bits. In the extended safety vector model, each node knows fault information within distance-2; fault information outside distance-2 is coded in a special way based on the coded information of its neighbors. The extended safety vector of each node can be easily calculated through n-1 rounds of information exchanges among neighboring nodes. Therefore, each extended safety vector is an approximated measure of the number & distribution of faults in the neighborhood. Optimal unicasting between two nodes is guaranteed if the kth bit of the safety vector of the source node is one, where k is the Hamming distance between the source & destination nodes. In addition, the extended safety vector can be used as a navigation tool to direct a message to its destination through a minimal path. A simulation study has been conducted based on different selections of d, and results have shown a significant improvement under the proposed model over the safety vector model in handling link faults, even for a small value of d as in the extended safety vector model where d=2. View full abstract»

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  • Circular sequential k-out-of-n congestion system

    Publication Year: 2005 , Page(s): 412 - 420
    Cited by:  Papers (10)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (296 KB) |  | HTML iconHTML  

    A circular sequential k-out-of-n congestion (CSknC) model is presented. This model finds use in reliable systems to prevent single-point failure, such as (k,n) secret key sharing systems. The model assumes that each of the n servers has a known congestion probability. These n servers are arranged in a circle, and are connected sequentially. A server is connected successfully if it is not congested. Previously connected servers are blocked from reconnecting. Congested servers have to be reconnected until k servers are connected successfully. We present the recursive, and marginal formulas for the probability of success, as well as the average number of connection attempts needed with k successfully connected servers. The optimal arrangement of servers is specified to minimize the average number of connection attempts. These formulas can be used to rearrange the servers adaptively when the initial congestion probabilities are not known. Compared to the circular CknG systems, the CSknC systems are shown to have a higher success probability, and require less connection attempts with k successfully connected servers. View full abstract»

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  • Reliability optimization of distributed access networks with constrained total cost

    Publication Year: 2005 , Page(s): 421 - 430
    Cited by:  Papers (14)
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    In this paper, we study the system reliability optimization of distributed access networks subject to a constraint on the total cost. We first formulate the cost-constrained system reliability optimization problem as a searching process in a combinatorial tree, which enumerates all the possible solutions to the problem. Because the calculation of each possible solution for the reliability problem is extremely time-consuming, a novel algorithm, the Shrinking & Searching Algorithm (SSA), is proposed to speed up the searching process. SSA jointly considers the upper bound of the system reliability for each branch in the combinatorial tree, and the cost constraint on the possible solutions. It avoids most of the redundant calculations in the searching process by gradually shrinking the difference between lower & upper bounds of the length of a path in the corresponding combinatorial tree, which represents a feasible solution. Case study & simulation results are presented to demonstrate the performance of the SSA. View full abstract»

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  • Reliability of two-stage weighted-k-out-of-n systems with components in common

    Publication Year: 2005 , Page(s): 431 - 440
    Cited by:  Papers (18)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (288 KB) |  | HTML iconHTML  

    This paper extends the existing one-stage weighted-k-out-of-n model to two-stage weighted-k-out-of-n models with components in common. Algorithms are developed to calculate the system reliability, and generate the minimal cuts & minimal paths of two-stage weighted-k-out-of-n systems. Reliability bounds for systems with s-dependent component failures are investigated based on the generated minimal cuts & minimal paths. Two types of two-stage weighted-k-out-of-n models, the SW-k-out-of-n model, and the PW-k-out-of-n model, can be applied to investigate reliability issues in network applications, such as the project management, and the shortest path problems. Examples are provided to demonstrate the developed models & algorithms. View full abstract»

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  • Defect detection in analog and mixed circuits by neural networks using wavelet analysis

    Publication Year: 2005 , Page(s): 441 - 448
    Cited by:  Papers (15)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (408 KB) |  | HTML iconHTML  

    An efficient defect-oriented parametric test method for analog & mixed-signal integrated circuits based on neural network classification of a selected circuit's parameter using wavelet decomposition preprocessing is proposed in this paper. The neural network has been used for detecting catastrophic defects in two experimental analog & mixed-signal CMOS circuits by sensing the abnormalities in selected parameters, observed under defective conditions and by their consequent classification into a proper category. To reduce complexity of the neural network, wavelet decomposition is used to perform preprocessing of the analyzed parameter. Moreover, we show that wavelet analysis brings significant enhancement in the correct classification, and makes the neural network-based test method extremely efficient & versatile for detecting hard-detectable catastrophic defects in analog & mixed-signal circuits. View full abstract»

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  • On constructing the minimum orthogonal convex polygon for the fault-tolerant routing in 2-D faulty meshes

    Publication Year: 2005 , Page(s): 449 - 458
    Cited by:  Papers (19)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (448 KB) |  | HTML iconHTML  

    The rectangular faulty block model is the most commonly used fault model for designing fault-tolerant, and deadlock-free routing algorithms in mesh-connected multicomputers. The convexity of a rectangle facilitates simple, efficient ways to route messages around fault regions using relatively few or no virtual channels to avoid deadlock. However, such a faulty block may include many nonfaulty nodes which are disabled, i.e., they are not involved in the routing process. Therefore, it is important to define a fault region that is convex, and at the same time, to include a minimum number of nonfaulty nodes. In this paper, we propose an optimal solution that can quickly construct a set of minimum faulty polygons, called orthogonal convex polygons, from a given set of faulty blocks in a 2-D mesh (or 2-D torus). The formation of orthogonal convex polygons is implemented using either a centralized, or distributed solution. Both solutions are based on the formation of faulty components, each of which consists of adjacent faulty nodes only, followed by the addition of a minimum number of nonfaulty nodes to make each component a convex polygon. Extensive simulation has been done to determine the number of nonfaulty nodes included in the polygon, and the result obtained is compared with the best existing known result. Results show that the proposed approach can not only find a set of minimum faulty polygons, but also does so quickly in terms of the number of rounds in the distributed solution. View full abstract»

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  • Enhanced reliability of finite-state machines in FPGA through efficient fault detection and correction

    Publication Year: 2005 , Page(s): 459 - 467
    Cited by:  Papers (17)  |  Patents (7)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (408 KB) |  | HTML iconHTML  

    SRAM based FPGA are subjected to ion radiation in many operating environments. Following the current trend of shrinking device feature size & increasing die area, newer FPGA are more susceptible to radiation induced errors. Single event upsets (SEU), (also known as soft-errors) account for a considerable amount of radiation induced errors. SEU are difficult to detect & correct when they affect memory-elements present in the FPGA, which are used for the implementation of finite state machines (FSM). Conventional practice to improve FPGA design reliability in the presence of soft-errors is through configuration memory scrubbing, and through component redundancy. Configuration memory scrubbing, although suitable for combinatorial logic in an FPGA design, does not work for sequential blocks such as FSM. This is because the state-bits stored in flip-flops (FF) are variable, and change their value after each state transition. Component redundancy, which is also used to mitigate soft-errors, comes at the expense of significant area overhead, and increased power consumption compared to nonredundant designs. In this paper, we propose an alternate approach to implement the FSM using synchronous embedded memory blocks to enhance the runtime reliability without significant increase in power consumption. Experiments conducted on various benchmark FSM show that this approach has higher reliability, lower area overhead, and consumes less power compared to a component redundancy technique. View full abstract»

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  • Dependability evaluation of a fault-tolerant processor by GSPN modeling

    Publication Year: 2005 , Page(s): 468 - 474
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (192 KB) |  | HTML iconHTML  

    High dependability has become a paramount requirement for computing systems, as they are increasingly used in business & life critical applications. Advances in the design & manufacturing of semiconductor devices have increased the performance of computing systems at a dazzling pace. However, smaller transistor dimensions, lower power voltages, and higher operating frequencies have negatively impacted dependability by increasing the probability of occurrence of transient & intermittent faults. This paper discusses the main trends in dependability of semiconductor devices, and presents a candidate architecture for a fault-tolerant microprocessor. Dependability of the processor is analyzed, and the advantages provided by fault tolerance are underscored. The effect of the higher rates of occurrence of the transient & intermittent faults on a typical microprocessor is evaluated with the aid of GSPN modeling. Dependability analysis shows that a five times increase of the rate of occurrence of the transients leads to about five time lower MTBF, if no error recovery mechanisms are employed. Significantly lower processor availability is also observed. The fault-tolerant processor is devised to mitigate the impact of the higher transient & intermittent fault rates. The processor is based on core redundancy & state checkpointing, and supports three levels of error recovery. First, recovery from a saved state (SSRC) is attempted. The second level consists of a retry (SSRR), and is activated when the first level of recovery fails. Processor reset, followed by reintegration under the operating system control (RB), is the third level of recovery. Dependability analysis, based on GSPN, shows that fault-tolerance features of the processor preserve the MTBF, even if the rate of the transient faults nearly doubles. In terms of availability, a four-time increase of the rate of occurrence of the transients is compensated. The effect of intermittent faults is also analyzed. A five-time increase of the failure rate of the intermittent faults may lower MTBF by 31% to 33%. MTBF decreases even more, by 45% to 67%, if bursts of errors are considered. Intermittent faults have a negative impact on availability as well. Maintaining the dependability of complex integrated circuits t- o the level available today is becoming a challenge as semiconductor integration continues at a fast pace. Fault avoidance techniques, mainly based on process technology & circuit design, will no be able to fully mitigate the impact of higher rates of occurrence of transient & intermittent faults. As a result, fault-tolerant features, specific to custom designed components today, ought to be employed by COTS circuits, in the future. Enhanced concurrent error detection & correction, self checking circuits, space & time redundancy, triplication, and voting all need to be integrated into semiconductor devices in general, and microprocessors in particular, in order to improve fault & error handling. View full abstract»

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  • Quality-reliability chain modeling for system-reliability analysis of complex manufacturing processes

    Publication Year: 2005 , Page(s): 475 - 488
    Cited by:  Papers (9)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (424 KB) |  | HTML iconHTML  

    System reliability of a manufacturing process should address effects of both the manufacturing system (MS) component reliability, and the product quality. In a multi-station manufacturing process (MMP), the degradation of MS components at an upstream station can cause the deterioration of the downstream product quality. At the same time, the system component reliability can be affected by the deterioration of the incoming product quality of upstream stations. This kind of quality & reliability interaction characteristics can be observed in many manufacturing processes such as machining, assembly, and stamping. However, there is no available model to describe this complex relationship between product quality, and MS component reliability. This paper, considering the unique complex characteristics of MMP, proposes a new concept of quality & reliability chain (QR-Chain) effect to describe the complex propagation relationship of the interaction between MS component reliability, and product quality across all stations. Based on this, a general QR-chain model for MMP is proposed to integrate the product quality with the MS component reliability information for system reliability analysis. For evaluation of system reliability, both the exact analytic solution, and a simpler upper bound solution are provided. The upper bound is proved to be equal to the exact solution if the product quality does not have self-improvement, which is generally true in many MMP. Therefore, the developed QR-chain model, and its upper bound solution can be applied to many MMP. View full abstract»

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  • Marginally monotonic maintenance policies for a multi-state deteriorating machine with probabilistic monitoring, and silent failures

    Publication Year: 2005 , Page(s): 489 - 497
    Cited by:  Papers (13)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (320 KB) |  | HTML iconHTML  

    We characterize the structure of optimal policies for maintenance & replacement actions over a finite horizon. The context is machine monitoring when the following are true: 1) The machine can operate in one of N states in S∈{0,1,...,N-1} where 0 is good, 1 to N-2 represent increasing levels of deterioration (i.e., the system becomes increasingly worn, but is still able to produce usable parts), and N-1 is bad (or failed). 2) Observations are related probabilistically to the state of the process. 3) The machine's state is known with certainty only immediately after a replacement. The last assumption, consistent with "silent" failures, distinguishes our results from others. We prove [using the theory & results of partially observable Markov decision processes (POMDP)] that the policy that minimizes the total expected cost of system maintenance has a "marginally monotonic" structure. The concept of "marginal monotonicity", which requires a component-wise partial ordering, and monotonicity of the expected total cost function with respect to each component of the state space, allows characterization of the policy that minimizes the total expected cost. This feature allows us to represent the optimal policy by a collection of decision rules characterized by at most N functions. View full abstract»

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  • Dependability metrics to assess safety-critical systems

    Publication Year: 2005 , Page(s): 498 - 505
    Cited by:  Papers (15)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (256 KB) |  | HTML iconHTML  

    Metrics are commonly used in engineering as measures of the performance of a system for a given attribute. For instance, in the assessment of fault tolerant systems, metrics such as the reliability, R(t) and the Mean Time To Failure (MTTF) are well-accepted as a means to quantify the fault tolerant attributes of a system with an associated failure rate, λ. Unfortunately, there does not seem to be a consensus on comparable metrics to use in the assessment of safety-critical systems. The objective of this paper is to develop two metrics that can be used in the assessment of safety-critical systems, the steady-state safety, Sss, and the Mean Time To Unsafe Failure (MTTUF). Sss represents the evaluation of the safety as a function of time, in the limiting case as time approaches infinity. The MTTUF represents the average or mean time that a system will operate safely before a failure that produces an unsafe system state. A 3-state Markov model is used to model a safety-critical system with the transition rates computed as a function of the system coverage Csys, and the hazard rate λ(t). Also, λ(t) is defined by the Weibull distribution, primarily because it allows one to easily represent the scenarios where the failure rate is increasing, decreasing, and constant. The results of the paper demonstrate that conservative estimates for lower bounds for both Sss & the MTTUF result when Csys is assumed to be a constant regardless of the behavior of λ(t). The derived results are then used to evaluate three example systems. View full abstract»

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  • Computing steady-state mean time to failure for non-coherent repairable systems

    Publication Year: 2005 , Page(s): 506 - 516
    Cited by:  Papers (8)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (488 KB) |  | HTML iconHTML  

    Mean time to failure (MTTF) is an important reliability measure. Previous research is mainly concerned with the MTTF computation of coherent systems. In this paper, we derive equations to calculate the steady-state MTTF for noncoherent systems. Based on the equations, we extend the BDD by adding an intersection edge in each BDD node to efficiently store additional information for MTTF computation of noncoherent systems. A recursive algorithm is developed for MTTF computation using the extended BDD. To accelerate building the extended BDD, a method is proposed to avoid calculating the intersection edge for some nodes by keeping node monotonicity during the BDD construction. We show the efficiency of our algorithm by applying it to some example fault trees, real-life applications, and large fault tree benchmarks. View full abstract»

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  • Composite importance measures for multi-state systems with multi-state components

    Publication Year: 2005 , Page(s): 517 - 529
    Cited by:  Papers (53)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (536 KB) |  | HTML iconHTML  

    This paper presents & evaluates composite importance measures (CIM) for multi-state systems with multi-state components (MSMC). Importance measures are important tools to evaluate & rank the impact of individual components within a system. For multi-state systems, previously developed measures do not meet all user needs. The major focus of the study is to distinguish between two types of importance measures which can be used for evaluating the criticality of components in MSMC with respect to multi-state system reliability. This paper presents Type 1 importance measures that are involved in measuring how a specific component affects multi-state system reliability. A Monte Carlo (MC) simulation methodology for estimating the reliability of a MSMC is used for computing the proposed CIM metrics. Previous approaches (Type 2) have focused on investigating how a particular component state or set of states affects multi-state system reliability. For some systems, it is not clear how to prioritize system component importance, collectively considering all of its states, using the previously developed importance measures. That detracts from those measures. Experimental results show that the proposed CIM can be used as an effective tool to assess component criticality for MSMC. Examples are used to illustrate & compare the proposed CIM with previous multi-state importance measures. View full abstract»

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  • New cumulative damage models for failure using stochastic processes as initial damage

    Publication Year: 2005 , Page(s): 530 - 540
    Cited by:  Papers (10)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (392 KB) |  | HTML iconHTML  

    Based on a generalized cumulative damage approach with a stochastic process describing initial damage for a material specimen, a broad class of statistical models for material strength is developed. Plausible choices of stochastic processes for the initial damage include Brownian motion, geometric Brownian motion, and the gamma process; and additive & multiplicative cumulative damage functions are considered. The resulting general statistical model gives an accelerated test form of the inverse Gaussian distribution, special cases of which include some existing models in addition to several new models. Model parameterizations & estimation by maximum likelihood from accelerated test data are discussed, and the applicability of the general model is illustrated for three sets of strength data. The proposed models are compared with the power-law Weibull model, and the inverse Gaussian generalized linear models. View full abstract»

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  • A workload-based analysis of software aging, and rejuvenation

    Publication Year: 2005 , Page(s): 541 - 548
    Cited by:  Papers (35)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (216 KB) |  | HTML iconHTML  

    We present a hierarchical model for the analysis of proactive fault management in the presence of system resource leaks. At the low level of the model hierarchy is a degradation model in which we use a nonhomogeneous Markov chain to establish an explicit connection between resource leaks, and the failure rate. With the degradation model, we prove that the failure rate is asymptotically constant in the absence of resource leaks, and it is increasing as leaks occur & accumulate, which confirms the resource leaks as an aging source. The proactive fault management (PFM) is modeled at the higher level as a semi-Markov process. The PFM model takes as input the degradation analysis from the low-level model, and allows us to determine optimal rejuvenation schedules with respect to various system measures. View full abstract»

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  • Penalty function approach in heuristic algorithms for constrained redundancy reliability optimization

    Publication Year: 2005 , Page(s): 549 - 558
    Cited by:  Papers (10)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (464 KB) |  | HTML iconHTML  

    To solve the problem of constrained redundancy reliability optimization, several heuristic algorithms have been developed in the literature. Most of these algorithms search for the solutions remaining within the feasible boundary e.g. [15], [20]. Perhaps the most interesting & efficient heuristic algorithm in terms of solution quality is that given by KYA, in which the search is made not only in the feasible region but also into the bounded infeasible region by making an excursion, which returns to the feasible region with a possibly improved solution. In this paper, a heuristic algorithm based on the penalty function approach is proposed to solve the constrained redundancy optimization problem for complex systems. An excursion is made into the infeasible region, but an adaptive penalty function helps the search not to go too far into the infeasible region. Thus, promising feasible & infeasible regions of the search space are explored efficiently & effectively to identify finally an optimal or near optimal solution. Computational experiments are conducted on 11 sets of problems (10 with linear constraints, and 1 with nonlinear constraints); each with 10 different randomly generated initial solutions. Comparison is made between the proposed algorithm P-Alg, N-N algorithm [15], Shi algorithm [20], and KYA [9] . It is observed that P-Alg performs consistently better than others, showing an overall improvement in various measures of performance. Besides, as P-Alg does not require any assumptions on the nature of the objective & constraint functions, it can solve a wide variety of problems. View full abstract»

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  • IEEE Transactions on Reliability information for authors

    Publication Year: 2005 , Page(s): 559 - 560
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    Freely Available from IEEE

Aims & Scope

IEEE Transactions on Reliability is concerned with the problems involved in attaining reliability, maintaining it through the life of the system or device, and measuring it.

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Meet Our Editors

Editor-in-Chief
Way Kuo
City University of Hong Kong