• Proceedings of the Korea Multimedia Society Conference
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• 2001.11a
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• pp.503-507
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• 2001

최근 개발되고 있는 SAN 기반 리눅스 클러스터 파일 시스템들은 중앙에 파일 서버 없이 디스크를 공유하는 클라이언트들이 화이버 채널을 통하여 마치 파일 서버처럼 디스크에 자유롭게 접근할 수 있으므로, 유용성, 부하의 균형, 확장성 등에서 장점을 가진다. 본 논문에서는 ETRI에서 개발중인 SAN 기반 리눅스 클러스터 파일 시스템인 SANtopia를 위해 설계된 새로운 mode의 구조와 이 inode의 구조를 기반으로 확장 해싱(Extendible Hashing)을 이용한 새로운 디렉토리 구조의 설계에 대하여 기술하고,성능 평가를 통하여 제안된 방법의 우수성을 보인다.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1995.04a
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• pp.646-655
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• 1995

본 연구에서는 기저역행렬의 계산방법에 따른 효율적인 자료구조를 실험적으로 검토하고, 입력자료방식과 효율화 방법을 제안하여 구현하였다. 기저역행렬의 계산방법에 따른 효율적인 자료구조는 명시형에서는 연결리스트 방식이 유리하였으며, 상하분해형에서는 연결 리스트 방법과 Gustavson 방법이 비슷한 효율을 보였다. 새로운 비영요소의 도입이 많은 경우일수록 연결 리스트가 효율적인 자료구조인 것으로 분석된다. 그리고 MPS자료의 입력방식과 효율화 방안에서는 각 열별로 행 정렬을 실시하고 해싱(hashing)함수를 도입하여 효율화를 기하였다.

• Proceedings of the Korean Information Science Society Conference
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• 2002.04b
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• pp.106-108
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• 2002

본 연구에서는 멀티미디어 데이터 검색에 클러스터링과 인덱싱 기법을 같이 적용하여 유사할 이미지끼리는 인접 디스크에 클러스터하고 이 클러스터에 접근하는 인덱스를 구축하여 검색이 빠르게 이루어지는 유사 검색방법을 제시한다. 이 연구에서는 트리 유사 구조의 인덱스 대신 해싱 방법을 이용하며 검색시 I/O시간을 줄이기 위해 오브젝트를 가진 클러스터 위치를 찾는데 한번의 I/O를 사용하고 이 클러스터를 읽기 위해 연속주인 파일 I/O를 사용하여 클러스터를 찾는 데용을 최소화한다 클러스터인덱싱 접근은 트리 유사 구조와 임의 I/O를 사용한 내용기반의 이미지 검색보다 효율적인 검색 적합성을 보이며 연속적 I/O를 통해 검색 미용을 낮춘다.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10a
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• pp.249-251
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• 1999

해싱 함수를 이용하여 작업을 여러 노드에 분할해서 실행하는 해쉬 기반 병렬 조인 기법에서 Data Skew는 특정 노드에 부하를 집중시키므로 시스템의 성능을 떨어뜨린다. 본 논문에서는 기본적인 해쉬 기반 조인 기법을 데이터 공유시스템에 적용하고, Data Skew를 해결하기 위하여 동적 작업 할당과 부하가 집중된 노드의 작업을 다른 노드로 재할당하는 작업 재배치 방법을 제안한다. 제안된 기법들의 성능을 분석하기 위하여 모의 실험을 수행하였으며, 모든 노드에서 데이터베이스가 저장된 디스크를 공유하는 데이터 공유 시스템의 겨우 동적 작업 할당과 작업 재배치 방법이 효과적임을 알 수 있었다.

• The KIPS Transactions:PartD
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• v.9D no.5
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• pp.779-788
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• 2002

There are many technically difficult issues in searching multimedia data such as image, video and audio because they are massive and more complex than simple text-based data. As a method of searching multimedia data, a similarity retrieval has been studied to retrieve automatically basic features of multimedia data and to make a search among data with retrieved features because exact match is not adaptable to a matrix of features of multimedia. In this paper, data clustering and its indexing are proposed as a speedy similarity-retrieval method of multimedia data. This approach clusters similar images on adjacent disk cylinders and then builds Indexes to access the clusters. To minimize the search cost, the hashing is adapted to index cluster. In addition, to reduce I/O time, the proposed searching takes just one I/O to look up the location of the cluster containing similar object and one sequential file I/O to read in this cluster. The proposed schema solves the problem of multi-dimension by using clustering and its indexing and has higher search efficiency than the content-based image retrieval that uses only clustering or indexing structure.

• The KIPS Transactions:PartA
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• v.13A no.1 s.98
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• pp.11-18
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• 2006

In the Internet of various networks, it is difficult to reduce real routing time by just minimizing their hop count. We propose an adaptive proximity route selection method in DHT-based peer-to-peer systems, in which nodes select the nぉe with smallest lookup latency among their routing table entries as a next routing node. Using Q-Routing algorithm and exponential recency-weighted average, each node estimates the total latency and establishes a lookup table. Moreover, without additional overhead, nodes exchange their lookup tables to update their routing tables. Several simulations measuring the lookup latencies and hop-to-hop latency show that our method outperforms the original Chord method as well as CFS' server selection method.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.9
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• pp.435-444
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• 2007

Caching web pages is an important part of web infrastructures. The effects of caching service are even more pronounced for wireless infrastructures due to their limited bandwidth. Medium to large-scale infrastructures deploy a cluster of servers to solve the scalability problem and hot spot problem inherent in caching. In this paper we present scheduling scheme based on cache utilization in a wireless internet proxy server cluster environment. The proposed method uses cache utilization for distributing evenly client requests to a cluster of cache servers and solving hot spot problem. We have implemented our approach and performed various experiments using publicly available traces. Experimental results on a cluster of 16 cache servers demonstrate that the proposed hashing method gives 45% to 114% Performance improvement over other widely used methods while addressing the hot spot problem.

• The KIPS Transactions:PartD
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• v.13D no.5 s.108
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• pp.651-660
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• 2006

Algorithms for mining association rules based on the Apriori algorithm use the hash tree data structure for storing and counting supports of the candidate frequent itemsets and the most part of the execution time is consumed for searching in the hash tree. The DHP(Direct Hashing and Pruning) algorithm makes efforts to reduce the number of the candidate frequent itemsets to save searching time in the hash tree. For this purpose, the DHP algorithm does preparative simple counting supports of the candidate frequent itemsets. At this time, the DHP algorithm uses the direct hash table to reduce the overhead of the preparative counting supports. This paper proposes and evaluates an efficient hashing mechanism for the direct hash table $H_2$ which is for pruning in phase 2 and the hash tree $C_k$, which is for counting supports of the candidate frequent itemsets in all phases. The results showed that the performance improvement due to the proposed hashing mechanism was 82.2% on the maximum and 18.5% on the average compared to the conventional method using a simple mod operation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.434-437
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• 2010

NIPS(Network Intrusion Prevention System) is in line at the end of the external and internal networks which performed two kinds of action: Signature-based filtering and anomaly detection and prevention-based on self-learning. Among them, a signature-based filtering is well known to defend against attacks. By using signature-based filtering, intrusion prevention system passing a payload of packets is compared with attack patterns which are signature. If match, the packet is discard. However, when there is packet delay, it will increase the required pattern matching time as the number of signature is increasing whenever there is delay occur. Therefore, to ensure the performance of IPS, we needed more efficient pattern matching algorithm for high-performance ISP. To improve the performance of pattern matching the most important part is to reduce the number of comparisons signature rules and the packet whenever the packets arrive. In this paper, we propose an improve signature hashing-based pattern matching method. We use tuple pruning algorithm with Bloom filters, which effectively remove unnecessary tuples. Unlike other existing signature hashing-based IPS, our proposed method to improve the performance of IPS.

• The Journal of the Convergence on Culture Technology
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• v.5 no.4
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• pp.407-412
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• 2019

In this paper, we propose a technique for processing of speech recognition in korean words. Speech recognition is a technology that converts acoustic signals from sensors such as microphones into words or sentences. Most foreign languages have less difficulty in speech recognition. On the other hand, korean consists of vowels and bottom consonants, so it is inappropriate to use the letters obtained from the voice synthesis system. That improving the conventional structure speech recognition can the correct words recognition. In order to solve this problem, a new algorithm was added to the existing speech recognition structure to increase the speech recognition rate. Perform the preprocessing process of the word and then token the results. After combining the result processed in the Levenshtein distance algorithm and the hashing algorithm, the normalized words is output through the consonant comparison algorithm. The final result word is compared with the standardized table and output if it exists, registered in the table dose not exists. The experimental environment was developed by using a smartphone application. The proposed structure shows that the recognition rate is improved by 2% in standard language and 7% in dialect.