• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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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.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.11b
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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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• v.26 no.3_4
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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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• v.14 no.3
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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.

• 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.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.3
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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.

• Journal of KIISE:Databases
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• v.27 no.1
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• pp.1-12
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• 2000

Many object oriented database systems manage object buffers to provide fast access to objects. Traditional buffer replacement algorithms based on fixed length pages simply assume that the cost incurred by operating a buffer is propertional to the number of buffer faults. However, this assumption no longer holds in an objects buffer where objects are of variable length and the cost of replacing an object varies for each object. In this paper, we propose a cost based replacement algorithm for object buffers. The proposed algorithm replaces the have minimum costs per unit time and unit space. The cost model extends the previous page based one to include the replacement costs and the sizes of objects. The performance tests show that proposed algorithm is almost always superior to the LRU-2 algorithm and in some cases is more than twice as fast. The idea of cost based replacement can be applied to any buffer management architectures that adopt earlier algorithms. It is especially useful in object oriented database systems where there is significant variation in replacement costs.

• IEMEK Journal of Embedded Systems and Applications
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• v.15 no.6
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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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• v.15 no.11
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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.

• KIISE Transactions on Computing Practices
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• v.21 no.1
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• pp.88-93
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• 2015

In modern computer systems, DRAM is commonly used as main memory due to its low read/write latency and high endurance. However, DRAM is volatile memory that requires periodic power supply (i.e., memory refresh) to sustain the data stored in it. On the other hand, PCM is a promising candidate for replacement of DRAM because it is non-volatile memory, which could sustain the stored data without memory refresh. PCM is also available for byte-addressable access and in-place update. However, PCM is unsuitable for using main memory of a computer system because it has two limitations: high read/write latency and low endurance. To take the advantage of both DRAM and PCM, a hybrid main memory, which consists of DRAM and PCM, has been suggested and actively studied. In this paper, we propose a novel page replacement algorithm for hybrid main memory. To cope with the weaknesses of PCM, our scheme focuses on reducing the number of PCM writes in the hybrid main memory. Experimental results shows that our proposed page replacement algorithm reduces the number of PCM writes by up to 80.5% compared with the other page replacement algorithms.