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민경훈,장혁수,Min, Gyeong-Hun,Jang, Hyeok-Su 한국정보처리학회 2000 정보처리논문지 Vol.7 No.7
Since most of the existing web cache structures are static, they cannot support the dynamic request change of he current WWW users well. Users re generally using multiple programs in several different windows with rapid preference change within a relatively short period of time. We develop a network-path based algorithm. It organizes a cache according to the network path of the requested URLs and build a network cache farm where caches are logically connected with each other and each cache has its own preference over certain network paths. The algorithm has been implemented and tested in a real site. The performance results show that the new algorithm outperforms the existing static algorithms in the hit ratio and response time dramatically.
An Intra-domain Network Topologyd Discovery Algorithm
민경훈,장혁수,Min, Gyeong-Hun,Jang, Hyeok-Su Korea Information Processing Society 2000 정보처리논문지 Vol.7 No.4
A network topology has been an important factor for an efficient network management, but data collection for the network configuration has been done manually or semi automatically by a network administrator or an expert. Requirements to generate an intro-domain network topology ar usually either all IP addresses with subne $t^ernet mask or the network identification of all IP addresses. The amounts of traffic are generally high in the semi-automatic system due to using large number of low-level protocols and commands to get rather simple data. In this paper, we propose an algorithm which can be executed with only publicly available input. It can find all IP addresses as well as the network boundary of an intra-domain by using an intelligent method developed in this algorithm. The collected data will be used to draw a network map automatically by using a proposed network topology generation algorithm.hm.
차원축소와 클러스터링을 동시에 적용한 데이터 분석 방법에 대한 연구
신병철(Byung-Cheol Shin),최승빈(Seung-Bin Choi),김보성(Bo-Sung Kim),배성민(Seong-Min-Bae),송성민(Seong-Min Song),장혁수(Hyeok-Su Jang),한동근(Dong-Geun Han),박세진(Se-Jin Park) ICT플랫폼학회 2023 ICT플랫폼학회 하계학술발표대회논문집 Vol.10 No.2
4차 산업혁명 시대로 넘어오며 데이터 분석이 중요해졌고 그 중 클러스터링과 같은 기술이 강조되고 있다. 본 논문에서 데이터 분석의 핵심요소인 클러스터링과 차원 분석 기법인 차원 축소에 대해 설명하고 클러스터링 차원에서 차원 축소를 적용했을 때 최대 약 2.95배 높은 실루엣 계수를 확인할 수 있다. 이를 통해 본 연구는 클러스터링과 차원 축소를 동시에 적용하였을 때 높은 성능 향상이 발생하고 저차원보다는 고차원에서 차원 축소가 더욱 효율적이라는 사실을 알 수 있다.