• Journal of KIISE:Computing Practices and Letters
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• v.16 no.3
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• pp.336-340
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• 2010

Flash storages are prevalent as portable storage in computing systems. When we consider the detachability of Flash storage devices, data integrity becomes an important issue. To assure extreme data integrity, file systems synchronously write all file data to storage accompanying hot write references. In this study, we concentrate on the effect of hot write references on Flash storage, and we consider the effect of absorbing the hot write references via nonvolatile write cache on the performance of the FTL schemes in Flash storage. In 80 doing, we quantify the performance of typical FTL schemes for workloads that contain hot write references through a wide range of experiments on a real system environment. Through the results, we conclude that the impact of the underlying FTL schemes on the performance of Flash storage is dramatically reduced by absorbing the hot write references via nonvolatile write cache.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06a
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• pp.218-220
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• 2012

인터넷 활용과 웹 어플리케이션의 개발이 증가함에 따라 처리해야하는 데이터의 양도 또한 증가하고 있다. 대량의 데이터를 효과적으로 처리하기 위한 방법 중 하나로 병렬처리 프로그래밍 모델인 맵리듀스가 있다. 하둡은 맵리듀스의 오픈소스 구현으로 대량의 데이터를 병렬로 처리하는 무료 자바 소프트웨어 프레임워크이다. 분산 파일 시스템을 사용하는 하둡에서는 처리하는 데이터가 다른 노드에 위치하는 데이터 로컬리티 문제가 전체 작업 수행시간의 증가를 야기하는 문제가 있다. 본 논문에서는 하둡에서의 데이터 로컬리티 문제를 해결하기 위한 데이터 복제기법을 제안한다. 제안하는 데이터 복제기법에서는 1) 라그랑지 보간법을 사용하여 과거 접근수를 이용한 미래 접근수를 예측하고, 2) 예측된 값을 Threshold값으로 설정하고, 3) 데이터 로컬리티 문제가 발생하였을 때, 복제사본을 생성할 것인지 캐시를 생성할 것인지를 결정하여 복제 사본의 수를 최적화 한다. 실험을 통해 단순히 복제사본 수를 증가시킴으로써 데이터 로컬리티를 향상을 이루어도 작업 완료시간이 감소하는 것이 아니라는 결과를 볼 수 있었고, 오버 런치로 인한 작업 완료시간 증가를 줄이기 위해 데이터 복제사본 수 최적화의 필요성을 확인할 수 있었다.

• Journal of KIISE
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• v.42 no.6
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• pp.723-733
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• 2015

The OTT service that provides multimedia video has spread over the Internet for terminals with a variety of resolutions. The terminals are in communication via a networks such as 3G, LTE, VDSL, ADSL. The service of the network has been increased for a variety of terminals giving rise to the need for a new way of encoding multimedia is increasing. SVC is an encoding technique optimized for OTT services. We proposed an efficient multimedia management system for the SVC encoded multimedia data. The I/O trace was generated using a zipf distribution, and were comparatively evaluated for performance with the existing system.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.4
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• pp.54-62
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• 2010

Semantic Web programming is such an immature area that it is yet based on API calls, and does not provide high productivity in compiler time and sufficient efficiency in runtime. To get over this limitation, some efforts have been devoted on dedicated programming languages for Semantic Web. In this paper, we introduce a sophisticated cashing technique to enhance the runtime efficiency of RDF (Resource Description Framework) processing programs with SPARQL queries. We use static program analysis on those programs to determine what to be cashed, so as to decrease the cash miss ratio. Our method is implemented on programs in 'Jey' language, which is one of the programming languages devised for RDF data processing.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.12
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• pp.149-155
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• 2012

SSD is a storage device of having high-performance controller and cache buffer and consists of many NAND flash memories. Because NAND flash memory does not support in-place update, valid pages are invalidated when update and erase operations are issued in file system and then invalid pages are completely deleted via garbage collection. However, garbage collection performs many erase operations of long latency and then it reduces I/O performance and increases wear leveling in SSD. In this paper, we propose a new method of de-duplicating valid data and recycling invalid data. The method de-duplicates valid data and then recycles invalid data so that it improves de-duplication ratio. Due to reducing number of writes and garbage collection, the method could increase I/O performance and decrease wear leveling in SSD. Experimental result shows that it can reduce maximum 20% number of garbage collections and 9% I/O latency than those of general case.

• The Journal of Society for e-Business Studies
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• v.15 no.4
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• pp.101-121
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• 2010

This paper presents an intelligent prefetching technique that significantly improves performance of hybrid fash-disk storage, a combination of flash memory and hard disk. Since flash memory embedded in a hybrid device is much faster than hard disk in terms of I/O operations, it can be utilized as a 'cache' space to improve system performance. The basic strategy for prefetching is to utilize sequential pattern mining, with which we can extract the access patterns of objects from historical access sequences. We use two techniques for enhancing the performance of hybrid storage with prefetching. One of them is to modify a FAST algorithm for mapping the flash memory. The other is to extend the unit of prefetching to a block level as well as a file level for effectively utilizing flash memory space. For evaluating the proposed technique, we perform the experiments using the synthetic data and real UCC data, and prove the usability of our technique.

• Journal of KIISE
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• v.42 no.9
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• pp.1109-1116
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• 2015

In this paper, we propose a query processing approach that uses the Spark functional programming and distributed memory system to solve the computational overhead of SPARQL. In the semantic web, RDF ontology data is produced at large scale, and the main challenge for the semantic web is to query and manipulate such a large ontology with a high throughput. The most existing studies on SPARQL have focused on deploying the Hadoop MapReduce framework, and although approaches based on Hadoop MapReduce have shown promising results, they achieve a low level of throughput due to the underlying distributed file processes. Therefore, in order to speed up the query processes, we suggest query- processing methods that are based on memory caching in distributed memory system. Our approach is also integrated with a clause unification method for propagating between the clauses that exploits Spark join, map and filter methods along with caching. In our experiments, we have achieved a high level of performance relative to other approaches. In particular, our performance was nearly similar to that of Sempala, which has been considered to be the fastest query processing system.

• Journal of Advanced Navigation Technology
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• v.23 no.2
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• pp.158-165
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• 2019

The existing web page was downloaded and provided to the user every time the user requested the page. Therefore, if the same page is repeatedly requested by the user, only the download for the same resource is repeated. This is a factor that causes unnecessary consumption of data. We focus on reducing data consumption caused by unnecessary requests between users and servers, and improving content delivery speed. Therefore, in this paper, we propose a caching system and an algorithm that can reduce the data consumption while maintaining the latest cache by comparing the hash value using the hash function that can detect the change of the file requested by the user.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.7
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• pp.209-216
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• 2023

Modern HPC systems are equipped with many-core CPUs with dozens of cores. When performing parallel I/O in such a system, there is a limit to scalability due to the problem of the LRU lock management policy of the Linux system. The study proposes an improved FinerLRU to solve this problem. Our new FinerLRU improves the parallel write performance of file systems using the buffer cache through granular lock management by increasing the number of LRU locks upto the maximum number of cores. The proposed method was implemented in Linux 5.18.11, and the performance was measured on two types of CPUs, Intel Icelake Xeon and Intel Knights landing, with different characteristics, and it was found that a performance improvement of about two times can be obtained in both types of systems.

• Journal of Internet Computing and Services
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• v.6 no.2
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• pp.69-84
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• 2005

As the Internet users are increasing rapidly, a cluster web server system is attracted by many researchers and Internet service providers. The cluster web server has been developed to efficiently support a larger number of users as well as to provide high scalable and available system. In order to provide the high performance in the cluster web server, efficient load distribution is important, and recently many content-aware request distribution techniques have been proposed. In this paper, we propose a new content-aware load balancing technique that can evenly distribute the workload to each node in the cluster web server. The proposed technique is based on the hash histogram transformation, in which each URL entry of the web log file is hashed, and the access frequency and file size are accumulated as a histogram. Each user request is assigned into a node by mapping of (hashed value-server node) in the histogram transformation. In the proposed technique, the histogram is updated periodically and then the even distribution of user requests can be maintained continuously. In addition to the load balancing, our technique can exploit the cache effect to improve the performance. The simulation results show that the performance of our technique is quite better than that of the traditional round-robin method and we can improve the performance more than $10\%$ compared with the existing workload-aware load balancing(WARD) method.