• Journal of Korean Institute of Industrial Engineers
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• v.39 no.4
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• pp.233-238
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• 2013

This article concerns a profit model in a repair limit replacement problem with imperfect repair. If a system fails, we should decide whether we repair the failed system (repair option) or replace it by new one (replacement option with a lead time). We assume that repair times are random variables and can be estimated before repair with estimation error. If the estimated repair time is less than the specified limit (repair time limit), the failed unit is repaired but the unit after repair is different from the new one (imperfect repair). Otherwise, we order a new unit to replace the failed unit. The long run average profit (expected profit rate) is used as an optimization criterion and the optimal repair time limit maximizes the expected profit rate. Some special cases are derived.

• The KIPS Transactions:PartA
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• v.13A no.6 s.103
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• pp.511-516
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• 2006

The data grid computing provides geographically distributed storage resources to solve computational problems with large-scale data. Unlike cache replacement policies in virtual memory or web-caching replacement, an optimal file replacement policy for data grids is the one of the important problems by the fact that file size is very large. The traditional file replacement policies such as LRU(Least Recently Used) LCB-K(Least Cost Beneficial based on K), EBR(Economic-based cache replacement), LVCT(Least Value-based on Caching Time) have the problem that they have to predict requests or need additional resources to file replacement. To solve theses problems, this paper propose SBR-k(Sized-based replacement-k) that replaces files based on file size. The results of the simulation show that the proposed policy performs better than traditional policies.

• The Transactions of the Korea Information Processing Society
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• v.3 no.7
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• pp.1669-1679
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• 1996

In this paper, we address the problem of how to replace huffers in multimedia database systems with time-varying skewed data access. The access pattern in the multimedia database system to support audio-on-demand and video-on-demand services is generally skewed with a few popular objects. In addition the access pattem of the skewed objects has a time-varying property. In such situations, our analysis indicates that conventional LRU(least Recently Used) and LFU(Least Frequently Used) schemes for buffer replacement algorithm(ABRN:Adaptive Buffer Replacement using Neural suited. We propose a new buffer replacement algorithm(ABRN:Adaptive Buffer Replacement using Neural Networks)using a neural network for multimedia database systems with time-varying skewed data access. The major role of our neural network classifies multimedia objects into two classes:a hot set frequently accessed with great popularity and a cold set randomly accessed with low populsrity. For the classification, the inter-arrival time values of sample objects are employed to train the neural network.Our algorithm partitions buffers into two regions to combine the best roperties of LRU and LFU.One region, which contains the 핫셋 objects, is managed by LFU replacement and the other region , which contains the cold set objects , is managed by LRUreplacement.We performed simulation experiments in an actual environment with time-varying skewed data accsee to compare our algorithm to LRU, LFU, and LRU-k which is a variation of LRU. Simulation resuults indicate that our proposed algorthm provides better performance as compared to the other algorithms. Good performance of the neural network-based replacement scheme means that this new approach can be also suited as an alternative to the existing page replacement and prefetching algorithms in virtual memory systems.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.6
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• pp.1091-1101
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• 2015

Cache mechanism, which has been a research subject for a significant period of time in computer science, has become realized in the form of web caching in network practice. Web caching has various advantages, such as saving of network resources and response time reduction, depends its performance on cache replacement policy, therefore, analysis and consideration of the environment in which a web cache operates is essential for designing better replacement policies. Thus, in the current web environment where is rapidly changing relative to the past, a new cache replacement policy is necessary to reflect those changes. In this paper we stipulate some characteristics of the web at present, propose a new cache replacement policy, and evaluate it.

• Journal of Korean Society for Quality Management
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• v.32 no.3
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• pp.62-67
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• 2004

This paper presents and compares two block replacement policies under random use durations. The units are put in service altogether and then idle for some time. The time durations during which units are put in service are random variables. Two block replacement policies, called N-policy and T-policy, are presented. Under N-policy, units are replaced altogether after the Nth use. Under T-policy, units are replaced altogether at the end of the use after cumulative use time T elapses. The failures during use durations are replaced by new ones individually. The cost rate expressions under the policies are derived for exponential use durations. Numerical examples are presented to compare the performances of the two policies.

• Journal of the Korean Data and Information Science Society
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• v.17 no.3
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• pp.743-752
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• 2006

This paper considers a Bayesian approach to replacement policy model with minimal repair. We use the criterion based on the expected cost and the expected downtime to determine the optimal replacement period. To do so, we obtain the expected cost rate per unit time and the expected downtime per unit time, respectively. When the failure time is Weibull distribution with uncertain parameters, a Bayesian approach is established to formally express and update the uncertain parameters for determining an optimal maintenance policy. Especially, the overall value function suggested by Jiagn and Ji(2002) is applied to obtain the optimal replacement period. The numerical examples are presented for illustrative purpose.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.8
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• pp.527-534
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• 2013

The software is changed according to the changing businesses and the user requirement, it involves increasing complexity and cost. Considering the repetitive changes required for the software, replacement is more efficient than maintenance at some point. In this study, the replacement time was predicted using the service dissatisfaction index and replacement point assessment index by the software group for each task. First, fuzzy inference was used to develop the method and indicator for the user's service level dissatisfaction. Second, the replacement point assessment method was established considering the quality, costs, and new technology of the software. Third, a replacement time prediction technique that used the gap between the user service measurement and replacement point assessment values was proposed. The results of the case study with the business solutions of three organizations, which was conducted to verify the validity of the proposed prediction technique in this study, showed that the service dissatisfaction index decreased by approximately 16% and the replacement point assessment index increased by approximately 9%.

• The Journal of the Korea Contents Association
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• v.8 no.11
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• pp.57-64
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• 2008

The data grid computing provides geographically distributed storage resources to solve computational problems with large-scale data. Unlike cache replacement policies in virtual memory or web-caching replacement, an optimal file replacement policy for data grids is the one of the important problems by the fact that file size is very large. The traditional file replacement policies such as LRU(Least Recently Used), LCB-K(Least Cost Beneficial based on K), EBR(Economic-based cache replacement), LVCT(Least Value-based on Caching Time) have the problem that they have to predict requests or need additional resources to file replacement. To solve theses problems, this paper propose SBR-k(Sized-based replacement-k) that replaces files based on file size. The proposed policy considers file size to reduce the number of files corresponding to a requested file rather than forecasting the uncertain future for replacement. The results of the simulation show that hit ratio was similar when the cache size was small, but the proposed policy was superior to traditional policies when the cache size was large.

• Journal of the military operations research society of Korea
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• v.10 no.2
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• pp.61-73
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• 1984

A block replacement policy using items with different reliability is discussed. We divide system unit failure modes into two modes and use less reliable unit when operating unit fails near the planned preventive replacement time. In this policy, item A has two failure modes. Mode-1 failure is removed by minimal repair, mode-2 failure by replacement. If mode-2 failure of item A happens in (0, $T-{\delta}$), failure item A is replaced by new item A. If mode-2 failure of item A happens in ($T-{\delta}$, T), failure item A is replaced by new item B. Item B should be cheaper and less durable than item A. Under this policy, we determine the preventive replacement interval $T^{*}$ and the interval ${\delta}^{*}$ of item B replacement which minimize the cost rate per unit time.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.10 no.16
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• pp.75-80
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• 1987

This paper is deals with the preventive replacement for the equipment which fails only when the total amount of damage reaches a prespecified failure level. Most of replacement model use time as their decision variable, but it is not appropriate for the cases in which failures dependent on their cumulative damage levels. In this paper, a new type preventive replacement model is introduced in which an equipment is replaced before failure when the cumulative damage reaches a certain level or replaced on failure, whichever occures first. The optimal replacement damage levels which minimize total expected cost are obtained by the Dynamic programming Method when the number of use of the equipment is finite. A numerical example is also presented. The optimal preventive replacement policy when the equipment will be used for a finite time span is also discussed.