• Proceedings of the Korean Information Science Society Conference
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• 2005.11b
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• pp.211-213
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• 2005

데이터 웨어하우스는 축적된 대량의 데이터를 분석하여 의사결정을 지원하는 시스템이다. 의사결정을 위한 대량의 데이터 분석은 많은 비용을 요구하므로, 질의 처리 성능을 높이고 의사 결정자에게 빠른 응답을 제공하는 효율적인 데이터 큐브 생성 기법이 연구되었다. 기존 기법으로는 Multiway Array 기법과 H-Cubing 기법이 있다. Multiway Array 기법은 다차원 집계 연산에 필요한 모든 데이터를 배열로 저장하는 것으로 데이터의 양이 많아질수록 메모리 사용이 증가한다. H-Cubing 기법은 Hyper-Tree를 기반으로 튜플을 트리로 구축하므로 모든 튜플을 트리로 구축해야 하는 비용이 증가한다. 본 논문에서는 데이터 웨어하우스에서 해쉬 테이블을 이용한 효율적인 데이터 큐브 생성 기법을 제안한다. 제안 기법은 데이터 큐브 생성 시 필드 해쉬 테이블과 레코드 해쉬 테이블을 사용한다. 필드 해쉬 테이블은 저장될 레코드 순서 계산을 위하여 각 필드에 대해 레벨 값을 해쉬 테이블로 관리한다. 레코드 해쉬 테이블은 데이터 큐브 테이블에 저장될 레코드의 순서와 데이터 큐브 테이블에 저장하기 위한 임시 레코드의 위치를 관리한다. 필드 해쉬 테이블을 이용하여 다차원 데이터의 저장될 레코드 순서를 빠르게 찾아 저장함으로서 데이터 큐브의 생성속도가 향상된다. 또한 해쉬 테이블 만을 유지하면 되므로 메모리 사용량이 감소한다. 따라서 해쉬 테이블의 사용으로 데이터의 빠른 검색과 데이터 큐브 생성 요청에 빠른 응답이 가능하다.

• Journal of KIISE:Databases
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• v.31 no.2
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• pp.91-98
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• 2004

DHP mining association rules algorithm maintains previously independent direct hash table to reduce the sire of hash tree containing the frequency number of each candidate large itemset. It performs pruning by using the direct hash table when the hash tree is constructed. The mort large the size of direct hash table increases, the higher the effort of pruning becomes. Especially, the effect of pruning in phase 2 which generate 2-large itemsets is so high that it dominates the overall performance of DHP algorithm. So, following the speedy trends of producing VLM(Very Large Memory) systems, extreme increment of direct hash table size is being tried and one of those trials is perfect hash table in phase 2. In case of using perfect hash table in phase 2, we found that some rearrangement of DHP algorithm got about 20% performance improvement compared to simply ｜H$_2$｜ reconfigured DHP algorithm. In this paper, we examine the feasibility of perfect hash table in phase 2 and propose PHP algorithm, a rearranged DHP algorithm, which uses the characteristics of perfect hash table sufficiently, then make an analysis on the results in experimental environment.

• Journal of Korea Multimedia Society
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• v.9 no.11
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• pp.1381-1394
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• 2006

Generation methods of data cube have been studied for many years in data warehouse which supports decision making using stored data. There are two previous studies, one is multi-way array algorithm and the other is H-cubing algorithm which is based on the hyper-tree. The multi-way array algorithm stores all aggregation data in arrays, so if the base data is increased, the size of memory is also grow. The H-cubing algorithm which is based on the hyper-tree stores all tuples in one tree so the construction cost is increased. In this paper, we present an efficient data cube generation method based on hash table using weight mapping table and record hash table. Because the proposed method uses a hash table, the generation cost of data cube is decreased and the memory usage is also decreased. In the performance study, we shows that the proposed method provides faster search operation time and make data cube generation operate more efficiently.

• The KIPS Transactions:PartC
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• v.16C no.4
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• pp.449-460
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• 2009

The signature hashing algorithm[9] provides the fast pattern matching speed for network IPS(Intrusion Prevention System) using the hash table. It selects 2 bytes from all signature rules and links to the hash table by the hash value. It has an advantage of performance improvement because it reduces the number of inspecting rules in the pattern matching. However it has a disadvantage of performance drop if the number of rules with the same hash value increases when the number of rules are large and the corelation among rules is strong. In this paper, we propose a method to make all rules distributed evenly to the hash table independent of the number of rules and corelation among rules for overcoming the disadvantage of the signature hashing algorithm. In the proposed method, it checks whether or not there is an already assigned rule linked to the same hash value before a new rule is linked to a hash value in the hash table. If there is no assigned rule, the new rule is linked to the hash value. Otherwise, the proposed method recalculate a hash value to put it in other position. We implemented the proposed method in a PC with a Linux module and performed experiments using Iperf as a network performance measurement tool. The signature hashing method shows performance drop if the number of rules with the same hash value increases when the number of rules are large and the corelation among rules is strong, but the proposed method shows no performance drop independent of the number of rules and corelation among rules.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.6
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• pp.137-145
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• 2010

Digital vessel have to accurate and efficient mange the digital data from various sensors in the digital vessel. But, In sensor network, it is difficult to transmit and analyze the entire stream data depending on limited networks, power and processor. Therefore it is suitable to use alternative stream data processing after classifying the continuous stream data. In this paper, We propose efficient processing method that arrange some sensors (temperature, humidity, lighting, voice) and process query based on sliding window for efficient input stream and pre-clustering using multiple Support Vector Machine(SVM) algorithm and manage hash table to summarized information. Processing performance improve as store and search and memory using hash table and usage reduced so maintain hash table in memory. We obtained to efficient result that accuracy rate and processing performance of proposal method using 35,912 data sets.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2004.03a
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• pp.11-16
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• 2004

최근 PDA와 같은 모바일 장치와 무선 인터넷의 사용이 확대되고, GPS의 개발로 인하여 위치 기반 서비스가 활발히 연구되고 있다. 그러나, 위치 기반 서비스의 중요한 요소인 이동 객체는 이동에 따른 갱신 비용이 높기 때문에 이전의 디스크 기반의 GIS에서 사용되던 인덱스를 이용하는 것은 효과적 이 지 못하다. 본 논문에서는 위치 기반 서비스를 위한 효과적인 현재 위치 데이타 처리를 위해 공간 해쉬 인덱스와 R-tree 인덱스를 결합한 형태인 HB(Hash Based)R-tree 인덱스를 개발하였다. HBR-tree 인덱스는 위치 기반 서비스에서 이동 객체의 위치 데이타가 빈번하게 갱신된다는 특징을 이용하여 갱신 작업은 HBR-tree 인덱스의 공간 해쉬 테이블 내에서 처리하고, 생성된 공간 해쉬 테이블을 이용하여 R-tree 인덱스를 구성함으로써 빠른 검색 질의 처리가 가능하고 갱신 비용을 줄일 수 있다는 장점이 있다.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.1202-1204
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• 2015

디지털 선박에서는 선박 내의 각종 센서로부터 측정된 디지털 데이터에 대한 정확하고 에너지 효율적인 관리가 필요하다. 본 논문에서는 디지털 선박 내에 다수 개의 센서(온도, 습도, 조도, 음성 센서)를 배치하고 효율적인 입력 스트림 처리를 위해서 슬라이딩 윈도우 기반으로 다중 Support Vector Machine(SVM) 알고리즘을 이용하여 사전 분류(pre-clustering)한 후 요약된 정보를 해쉬 테이블로 관리하는 효율적인 처리 기법을 제안한다. 해쉬 테이블을 이용하여 다차원 스트림 데이터의 저장될 레코드 순서를 빠르게 찾아 저장 및 검색함으로서 처리 속도가 향상되고 메모리에 해쉬 테이블 만을 유지하면 되므로 메모리 사용량이 감소한다. 35,912개의 데이터 집함을 사용하여 실험한 결과 제안 기법의 정확도와 처리 성능이 향상되었다.

• Journal of KIISE:Information Networking
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• v.36 no.2
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• pp.80-89
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• 2009

A DHT(Distributed Hash Table) based P2P is a method that compensates disadvantages of the existing unstructured P2P method. If a DHT algorithm is used, it can do fast data search and maintain search efficiency independent of the number of peers. The peers in a DHT method send messages periodically to keep the routing table updated. In a mobile environment, the peers in a DHT method should send messages more frequently to keep the routing table updated and reduce the failure of requests. However this results in increasing the overall network traffic. In this paper, we propose a method to reduce the update load of a routing table in the existing DHT by updating it in a reactive way. In the proposed reactive method, a routing table is updated only if a data request is coming whereas it is updated periodically in the existing proactive method. We perform experiments using Chord simulator(I3) made by UC Berkely. The experimental results show the performance improvement of the proposed method compared to the existing method.

• Communications of the Korean Institute of Information Scientists and Engineers
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• v.22 no.3
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• pp.18-25
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• 2004

• The KIPS Transactions:PartD
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• v.9D no.4
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• pp.579-586
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• 2002

This paper propose an efficient algorithm for mining association rules in the large main memory systems. To do this, the paper attempts firstly to extend the conventional algorithms such as DHP and Partition in order to be compatible to the large main memory systems and proposes secondly an algorithm to improve Partition algorithm by applying the techniques of the hash table and the bit map. The proposed algorithm is compared to the extended DHP within the experimental environments and the results show up to 65% performance improvement in comparison to the expanded DHP.