• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.1084-1089
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• 2004

This paper describes the improvement of web cache server by scoping in replacement algorithm of data which are collected from the clients. We have found that each replacement algorithm is suitable for each type of data in the web pages. Therefore, we introduce the mechanism to select the replacement algorithm depending on the size of data called the Replacement Algorithm Selection Mechanism (RASM). RASM allows the web cache server to have the suitable replacement algorithm for each type of data. As the result, the byte hit ratio of web cache server can be increased and the congestion in the network can be alleviated.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2003년도 추계학술발표논문집 (중)
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• pp.1007-1010
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• 2003

Efficient using of web cache is becoming important factor that decide system management efficiency in web-Based system. Cache performance depends heavily on replacement algorithms, which dynamically select a suitable subset of objects for caching in a finite space. However, replacement algorithm on web cache has many differences than traditional replacement algorithm. In this paper, a web-caching algorithm is proposed for efficient operation of web base system. The algorithm is designed based on a divided scope that considered size reference characteristic and heterogeneity on web object. The performance of the algorithm is analyzed with an experiment. With the experiment results, the algorithm is compared with previous replacement algorithms, and its performance is confirmed ith an improvement of response speed.

• Journal of applied mathematics & informatics
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• 제26권3_4호
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• pp.493-500
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• 2008

In this paper, we first construct a mathematical model for tagSNP selection based on LD measure $r^2$, then aiming at this kind of model, we develop an efficient algorithm, which is called approximate greedy algorithm. This algorithm is able to make up the disadvantage of the greedy algorithm for tagSNP selection. The key improvement of our approximate algorithm over greedy algorithm lies in that it adds local replacement(or local search) into the greedy search, tagSNP is replaced with the other SNP having greater similarity degree with it, and the local replacement is performed several times for a tagSNP so that it can improve the tagSNP set of the local precinct, thereby improve tagSNP set of whole precinct. The computational results prove that our approximate greedy algorithm can always find more efficient solutions than greedy algorithm, and improve the tagSNP set of whole precinct indeed.

• Journal of Information Processing Systems
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• 제14권3호
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• pp.631-644
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• 2018

Many studies on flash memory-based buffer replacement algorithms that consider the characteristics of flash memory have recently been developed. Conventional flash memory-based buffer replacement algorithms have the disadvantage that the operation speed slows down, because only the reference is checked when selecting a replacement target page and either the reference count is not considered, or when the reference time is considered, the elapsed time is considered. Therefore, this paper seeks to solve the problem of conventional flash memory-based buffer replacement algorithm by dividing pages into groups and considering the reference frequency and reference time when selecting the replacement target page. In addition, because flash memory has a limited lifespan, candidates for replacement pages are selected based on the number of deletions.

• 한국정보처리학회논문지
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• 제3권7호
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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.

• 한국지능시스템학회논문지
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• 제19권3호
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• pp.432-436
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• 2009

We have developed a new optimization algorithm termed simple bacteria cooperative optimization (sBCO) based on bacteria behavior patterns [1]. In [1], we have introduced the algorithm with basic operations and showed its feasibility with some function optimization problems. Since the sBCO was the first version with only basic operations, its performance was not so good. In this paper, we adopt a new operation, rank replacement, to the sBCO for improving its performance and compare its results to those of the simple genetic algorithm (sGA) which has been well known and widely used as an optimization algorithm. It was found from the experiments with four function optimization problems that the sBCO with rank replacement was superior to the sGA. This shows that our algorithm can be a good optimization algorithm.

• 한국정보과학회논문지:데이타베이스
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• 제27권1호
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• pp.1-12
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• 2000

많은 객체지향 데이타베이스 시스템들은 객체에 대한 빠른 액세스를 제공하기 위하여 객체 버퍼를 관리한다. 기존의 고정 길이의 페이지를 단위로 하는 교체 알고리즘들은 고정 크기의 페이지의 교체 비용이 일정하므로 버퍼에서 발생하는 비용이 단순히 버퍼 폴트 횟수에 비례한다고 가정하고 있다. 그러나, 객체 버퍼에서는 객체들의 크기와 교체 비용이 객체마다 다르므로 이러한 가정은 더이상 성립하지 않는다. 본 논문에서는 객체버퍼를 위한 비용기반 교체 알고리즘을 제안한다. 제안된 알고리즘은 객체들의 크기 와 교체 비용을 포함하도록 기존의 페이지 기반 모델을 확장한 비용 모텔을 기반으로 단위 시간 및 단위 공간당 비용이 최소가 되도록 하는 객체를 교체한다. 성능 평가 결과에 따르면 이 알고리즘은 기존의 LRU-2에 비해 거의 항상 우수하며 경우에 따라 2배 이상의 성능을 보인다. 비용기반 알고리즘은 기존의 방법들이 적용된 어떤 응용에도 쉽게 적용될 수 있으며, 특히 교체 비용이 일정하지 않은 객체지향 데이타베이스 시스템에서 효율적으로 활용될 수 있다.

• 대한임베디드공학회논문지
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• 제15권6호
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• pp.289-297
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• 2020

Although flash disks are being used widely instead of hard disks, it is difficult to optimize for effective utilization of flash disks because overwrite in place is impossible and the power consumption and time required for read, write, and erase operations are all different. One of these optimization issues is a cache management strategy to minimize write operations. The cache operates at two levels: an operating system equipped with flash disks and a translation layer within the flash disk. Most studies deal with the operating system-level cache strategy. In this study, we implement and analyse the DPW-LRU algorithm which is one of the recently proposed operating system cache replacement algorithms to apply to FTL, and grope with some improvements. As a result of the experiment, the DPW-LRU algorithm maintained superiority even in the FTL environment, and showed better performance with a slight improvement.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권11호
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• pp.3892-3912
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• 2021

The recent rapid growth of mobile network traffic places multi-access edge computing in an important position to reduce network load and improve network capacity and service quality. Contrasting with traditional mobile cloud computing, multi-access edge computing includes a base station cooperative cache layer and user cooperative cache layer. Selecting the most appropriate cache content according to actual needs and determining the most appropriate location to optimize the cache performance have emerged as serious issues in multi-access edge computing that must be solved urgently. For this reason, a cache placement algorithm based on comprehensive utility in big data multi-access edge computing (CPBCU) is proposed in this work. Firstly, the cache value generated by cache placement is calculated using the cache capacity, data popularity, and node replacement rate. Secondly, the cache placement problem is then modeled according to the cache value, data object acquisition, and replacement cost. The cache placement model is then transformed into a combinatorial optimization problem and the cache objects are placed on the appropriate data nodes using tabu search algorithm. Finally, to verify the feasibility and effectiveness of the algorithm, a multi-access edge computing experimental environment is built. Experimental results show that CPBCU provides a significant improvement in cache service rate, data response time, and replacement number compared with other cache placement algorithms.

• 정보과학회 컴퓨팅의 실제 논문지
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• 제21권1호
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• pp.88-93
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• 2015

DRAM은 빠른 쓰기/읽기 속도와 무한한 쓰기 횟수로 인해 컴퓨터 시스템에서 주로 메인 메모리로 사용되지만 저장된 데이터를 유지하기 위해 지속적인 전원공급이 필요하다. 반면, PCM은 비휘발성 메모리로 전원공급 없이 저장된 데이터를 유지할 수 있으며 DRAM과 같이 바이트 단위의 접근과 덮어쓰기가 가능하다는 점에서 DRAM을 대체할 수 있는 메모리로 주목받고 있다. 하지만 PCM은 느린 쓰기/읽기 속도와 제한된 쓰기 횟수로 인해 메인 메모리로 사용되기 어렵다. 이런 이유로 DRAM과 PCM의 장점을 모두 활용하기 위한 하이브리드 메인 메모리가 제안되었고 이에 대한 연구가 활발하다. 본 논문에서는 DRAM과 PCM으로 구성된 하이브리드 메인 메모리를 위한 새로운 페이지 교체 기법을 제안한다. PCM의 단점을 보완하기 위해 제안 기법은 PCM 쓰기 횟수를 줄이는 것을 목표로 하며 실험결과에서 알 수 있듯이 본 논문의 제안 기법은 다른 페이지 교체 기법에 비해 PCM 쓰기 횟수를 80.5% 줄인다.