• Journal of KIISE:Computer Systems and Theory
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• v.27 no.8
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• pp.730-740
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• 2000

The software rejuvenation method for highly available multiplex systems uses a pro-active fault-tolerant approach to handle system failures. The software rejuvenation prevents failures from occurring, while the previous methods recover from failures after happening. Especially, since the software aging proceeds fast in the software used for the multimedia mobile computing due to the loss of communications or data, the preventive method from failures using software rejuvenation can be used for the multimedia mobile computing. In this paper, according to the operational parameters such as rejuvenation period, rejuvenation time, failure rate and repair rate of the servers, number of running servers, duration of running time, and type of running modes, we calculate steady-state probabilities, downtime, availability, and cost of the multiplex systems using software rejuvenation method. We validate the closed-form solutions of the mathematical model by experiments based on various operational parameters and find that the software rejuvenation method can be adopted as preventive fault-tolerant technique. The failure rate and unstable rate of the servers are essential factors for the decision making of the rejuvenation policies.

• Proceedings of the Korea Contents Association Conference
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• 2005.11a
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• pp.423-427
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• 2005

It might be difficult to reduce failure rate for most of the cases are not available for debugging during operational phase, hence, there are some literatures to study that the failure rate is uniform throughout the operational time. The failure rate reduces and the reliability grows with time regardless of debugging. As a result, the products reliability varies with the time duration of these products in point of customer view. It accumulates the products experience, studies the efact operational method, and then finds and takes action against the fault circumstances. I propose the simple model to represent this status in this paper.

• Journal of Platform Technology
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• v.6 no.3
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• pp.47-54
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• 2018

Predictive analysis in the hardware industry can be performed at an appropriate point in time to prevent failure of production facilities and reduce management costs. This helps to perform more efficient and scientific maintenance through automation of failure analysis. Among them, predictive management aims to prevent the occurrence of anomalous state by identifying and improving the abnormal state based on the gathering, analysis, and scientific data management of facilities using information technology and constructing prediction model do. In this study, we made a fault tree through the Relex tool and analyzed the error code of the hardware to study the safety.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.40 no.8
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• pp.721-724
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• 2016

Because of the inherent uncertainties caused by the manufacturing process variations, future loading conditions, and incomplete damage models, the lifetimes of mechanical structures under field conditions are significantly different from the results obtained in the laboratories. In this study, a dual sensor was developed to prognosticate the fatigue failure of structures under these uncertain conditions, and its effectiveness was demonstrated on a rectangular columnar structure under repeated uni-axial loading. The dual sensor is a slightly weaker structure embedded in the target structure, so that failure occurs in the sensor earlier than in the target structure. From the signal differences in the strain gauges in the embedded dual sensor, it is possible to differentiate between the normal status and warning status, even under variable loads.

• Convergence Security Journal
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• v.12 no.6
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• pp.85-92
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• 2012

There are many software reliability models that are based on the times of occurrences of errors in the debugging of software. It is shown that it is possible to do asymptotic likelihood inference for software reliability models based on infinite failure model and non-homogeneous Poisson Processes (NHPP). For someone making a decision about when to market software, the conditional failure rate is an important variables. The finite failure model are used in a wide variety of practical situations. Their use in characterization problems, detection of outliers, linear estimation, study of system reliability, life-testing, survival analysis, data compression and many other fields can be seen from the many study. Statistical Process Control (SPC) can monitor the forecasting of software failure and there by contribute significantly to the improvement of software reliability. Control charts are widely used for software process control in the software industry. In this paper, we proposed a control mechanism based on NHPP using mean value function of log Poission, log-linear and Parto distribution.

• Journal of Digital Convergence
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• v.11 no.12
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• pp.319-326
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• 2013

There are many software reliability models that are based on the times of occurrences of errors in the debugging of software. Software error detection techniques known in advance, but influencing factors for considering the errors found automatically and learning factors, by prior experience, to find precisely the error factor setting up the testing manager are presented comparing the problem. It is shown that it is possible to do asymptotic likelihood inference for software reliability models based on infinite failure model and non-homogeneous Poisson Processes (NHPP). Statistical process control (SPC) can monitor the forecasting of software failure and thereby contribute significantly to the improvement of software reliability. Control charts are widely used for software process control in the software industry. In this paper, we proposed a control mechanism based on NHPP using mean value function of logarithmic hazard learning effects property.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.6
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• pp.483-490
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• 2015

There are many software reliability models that are based on the times of occurrences of errors in the debugging of software. It is shown that it is possible to do likelihood inference for software reliability models based on finite failure model and non-homogeneous Poisson Processes (NHPP). For someone making a decision about when to market software, the conditional failure rate is an important variables. The infinite failure model are used in a wide variety of practical situations. Their use in characterization problems, detection of outlier, linear estimation, study of system reliability, life-testing, survival analysis, data compression and many other fields can be seen from the many study. Statistical process control (SPC) can monitor the forecasting of software failure and thereby contribute significantly to the improvement of software reliability. Control charts are widely used for software process control in the software industry. In this paper, proposed a control mechanism based on NHPP using mean value function of Musa-Okumo and Power law type property.

• Journal of the Korea Society for Simulation
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• v.28 no.4
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• pp.1-10
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• 2019

The Sea Water Reverse Osmosis (SWRO) plant should take into account the availability of the plant from the design stage for long-term and continuous fresh water production. As it occurs, it is necessary to establish a corrective maintenance plan and preventive maintenance plan to maintain availability. In the field of complex engineering structures such as seawater desalination plants, it is difficult to estimate the reliability or availability of the system in a mathematical way. This study develops RAM analysis framework and model, and proposes discrete event simulation model as a application sowtware specialized for seawater desalination plant. Considering the characteristics of the plant maintenance, in case of corrective maintenance, we propose a preventive maintenance policy that not only repairs or replaces a single-broken part, but also simultaneously maintains all accessible parts according to the level of overhaul. A case study was conducted to estimate the availability of the system based on the field data of the seawater desalination plant in Korea and Saudi Arabia. The result was close to the expected availability of the plant.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.6
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• pp.178-186
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• 2020

In the domain of Korean weapon system development, issues about software reliability have become crucial factors when developing a weapon system. There is a process required for weapon system software development and management that includes certain activities required to improve the reliability of software. However, these activities are biased toward static and dynamic analyses of source code and do not include activities necessarily required by the international standard. IEEE std. 1633-2016 defines a process for software reliability engineering and describes software reliability estimation as an essential activity in the process. Software reliability estimation means that collecting defective data during the test and estimating software reliability by using the statistical model. Based on the estimated model, developers could estimate the failure rate and make comparisons with the objective failure rate to determine termination of the test. In this study, we collected defective data and applied reliability estimation models to analyze software reliability in the development of a weapon system. To achieve objective software reliability, we continuously tested our software and quantitatively calculated software reliability. Through the research, we hope that efforts to include activities described by the international standard will be carried out in the domain of Korean weapon system development.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.8B
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• pp.482-491
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• 2007

This paper proposes a k-disjoint-path routing algorithm that provides energy efficient and reliable message transmission in wireless sensor networks. The proposed algorithm sends messages through a single path without the occurrence of critical events. However, it sends through k disjoint paths(k>1) under the occurrence of critical events. The proposed algorithm detects the occurrence of critical events by monitoring changing data patterns, and calculates k from a well-defined fault model and the target-delivery ratio. Our simulations reveal that the proposed algorithm is more resilient to node failure than other routing algorithms, and it also decreases energy consumption and reduces the average delay much more than multi-path and path-repair algorithms.