• Title/Summary/Keyword: B+-Tree

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CL-Tree: B+ tree for NAND Flash Memory using Cache Index List (CL 트리: 낸드 플래시 시스템에서 캐시 색인 리스트를 활용하는 B+ 트리)

  • Hwang, Sang-Ho;Kwak, Jong Wook
    • Journal of the Korea Society of Computer and Information
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    • v.20 no.4
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    • pp.1-10
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    • 2015
  • NAND flash systems require deletion operation and do not support in-place update, so the storage systems should use Flash Translation Layer (FTL). However, there are a lot of memory consumptions using mapping table in the FTL, so recently, many studies have been proposed to resolve mapping table overhead. These studies try to solve update propagation problem in the nand flash system which does not use mapping table. In this paper, we present a novel index structure, called CL-Tree(Cache List Tree), to solve the update propagation problem. The proposed index structure reduces write operations which occur for an update propagation, and it has a good performance for search operation because it uses multi-list structure. In experimental evaluation, we show that our scheme yields about 173% and 179% improvement in insertion speed and search speed, respectively, compared to traditional B+tree and other works.

Insulation Reinforcement of the Electrical Power Cable Degradated by the Water Tree Using Silicon (실리콘을 이용한 수트리 열화된 전력 케이블의 절연 보강)

  • Kang, Hyeong-Gon;Park, Jun-Chae;Ko, Seok-Cheol;Lim, Sung-Hun;Lee, C.H.;Hanh, Y.B.;Han, B.S.
    • Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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    • 2003.07a
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    • pp.468-471
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    • 2003
  • Fault of under ground power cable occurs usually from the water tree such as the vented tree, the bow tree and the water-rich halo. The water tree penetrates to the polyethylene cable insulations. Sometimes, the water tree also diffuses to mother cable in the substation. In this paper, instead of replacement of the faulty cable, we tried to cure an electrical power cable degraded by the water trees with silicon injection method. And measured the results with the isothermal relaxation current analysis method. After cable cure, Chonil line was improved from 2.27 to 1.96 in a phase, from 2.148 to 2.020 in b phase, and from badness to 2.192 in c phase. And Keumam line was also improved from 2.419 to 1.920 in a phase, from 2.301 to 2.000 in b phase, and from badness to 1.957 in c phase.

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A New NTFS Anti-Forensic Technique for NTFS Index Entry (새로운 NTFS 디렉토리 인덱스 안티포렌식 기법)

  • Cho, Gyu-Sang
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.8 no.4
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    • pp.327-337
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    • 2015
  • This work provides new forensic techinque to a hide message on a directory index in Windows NTFS file system. Behavior characteristics of B-tree, which is apoted to manage an index entry, is utilized for hiding message in slack space of an index record. For hidden message not to be exposured, we use a disguised file in order not to be left in a file name attribute of a MFT entry. To understand of key idea of the proposed technique, we describe B-tree indexing method and the proposed of this work. We show the proposed technique is practical for anti-forensic usage with a real message hiding case using a developed software tool.

The Efficient Design and Implementation of The B-Tree on Flash Memory (플래시 메모리 상에서 효율적인 B-트리 설계 및 구현)

  • Nam Junghyun;Park Dong-Joo
    • Proceedings of the Korean Information Science Society Conference
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    • 2005.11b
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    • pp.55-57
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    • 2005
  • 최근 들어 PDA, 스마트카드, 휴대폰, MP3 플레이어 등과 같은 이동 컴퓨팅 장치의 데이터 저장소로 플래시 메모리를 많이 사용하고 있다. 이런 이동 컴퓨팅 장치의 데이터를 효율적으로 삽입$\cdot$삭제$\cdot$검색하기 위한 색인기법이 필요하다. 기존연구에서는 BFTL(B-Tree Flash Translation Layer)기법을 사용하여 플래시 메모리 상에 B-트리 구축 시 쓰기연산을 감소시켜 비용을 줄였지만, B-트리 검색비용과 하드웨어 구성비용이 증가한다는 단점을 가지고 있다. 본 논문에서는 기존 연구의 문제점을 개선하고 효율적으로 플래시 메모리상에 B-트리를 구현하기위해 BOF(B-Tree On Flash Memory)기법을 제안한다. 이 기법을 통해 BFTL 기법에 근접하는 구축비용을 얻을 수 있을 뿐만 아니라 상당한 검색비용을 줄일 수 있다. 또한 하드웨어적 비용도 고려하여 저비용으로 B-트리를 구현하였다.

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J-Tree: An Efficient Index using User Searching Patterns for Large Scale Data (J-tree : 사용자의 검색패턴을 이용한 대용량 데이타를 위한 효율적인 색인)

  • Jang, Su-Min;Seo, Kwang-Seok;Yoo, Jae-Soo
    • Journal of KIISE:Databases
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    • v.36 no.1
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    • pp.44-49
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    • 2009
  • In recent years, with the development of portable terminals, various searching services on large data have been provided in portable terminals. In order to search large data, most applications for information retrieval use indexes such as B-trees or R-trees. However, only a small portion of the data set is accessed by users, and the access frequencies of each data are not uniform. The existing indexes such as B-trees or R-trees do not consider the properties of the skewed access patterns. And a cache stores the frequently accessed data for fast access in memory. But the size of memory used in the cache is restricted. In this paper, we propose a new index based on disk, called J-tree, which considers user's search patterns. The proposed index is a balanced tree which guarantees uniform searching time on all data. It also supports fast searching time on the frequently accessed data. Our experiments show the effectiveness of our proposed index under various settings.

Image Processing of Treeing for Diagnosis of Deterioration in Submarine Cable (해저케이블의 열화진단을 위한 트리잉의 화상처리)

  • Lee, J.B.;Lim, J.S.;Park, H.B.;Gu, H.B.;Kim, T.S.;Yoshimura, N.
    • Proceedings of the KIEE Conference
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    • 1994.07b
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    • pp.1655-1657
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    • 1994
  • To measure treeing, visual measurement with an optical microscope has been used to explain breakdown mechanism by treeing in materials. The conventional direct visual method of tree deterioration observation is difficult to measure in short time processing, and impossible to analyze the deteriorated area by treeing, direction of tree growth, tree patterns etc. In this paper, we have developed a tree-measuring system using image processing for the tree growth, the area of deterioration, and other progresses of treeing. As experimental result, image processing is an effective alternative to direct visual observation method.

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Log-Structured B-Tree for NAND Flash Memory (NAND 플래시 메모리를 위한 로그 기반의 B-트리)

  • Kim, Bo-Kyeong;Joo, Young-Do;Lee, Dong-Ho
    • The KIPS Transactions:PartD
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    • v.15D no.6
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    • pp.755-766
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    • 2008
  • Recently, NAND flash memory is becoming into the spotlight as a next-generation storage device because of its small size, fast speed, low power consumption, and etc. compared to the hard disk. However, due to the distinct characteristics such as erase-before-write architecture, asymmetric operation speed and unit, disk-based systems and applications may result in severe performance degradation when directly implementing them on NAND flash memory. Especially when a B-tree is implemented on NAND flash memory, intensive overwrite operations may be caused by record inserting, deleting, and reorganizing. These may result in severe performance degradation. Although ${\mu}$-tree has been proposed in order to overcome this problem, it suffers from frequent node split and rapid increment of its height. In this paper, we propose Log-Structured B-Tree(LSB-Tree) where the corresponding log node to a leaf node is allocated for update operation and then the modified data in the log node is stored at only one write operation. LSB-tree reduces additional write operations by deferring the change of parent nodes. Also, it reduces the write operation by switching a log node to a new leaf node when inserting the data sequentially by the key order. Finally, we show that LSB-tree yields a better performance on NAND flash memory by comparing it to ${\mu}$-tree through various experiments.

DEhBT:A Multidimensional Data Partitioning Scheme using hB-tree (DEhBT: hB-tree를 이용한 다차원 데이타 분할 기법)

  • Kim, Dong-Yeon;O, Yeong-Bae;Choe, Dong-Hun;Han, Sang-Yeong;Lee, Sang-Gu
    • Journal of KIISE:Software and Applications
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    • v.26 no.1
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    • pp.16-24
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    • 1999
  • 본 논문에서는 병렬 DBMS를 사용하는 데이터 웨어하우스의 성능을 개선하기 위한 새로운 다차원 데이터 분할 기법을 제안한다. 데이터 웨어하우스는 많은 양의 데이터를 저장하는 대용량 데이터베이스이며 분석적인 정보를 얻기 위한 다차원 범위 질의가 대부분을 차지한다. 단일 차원분할 기법으로는 다차원 질의를 효과적으로 처리하기 어렵고 기존의 다차원 분할 기법은 임의의 알 수 없는 분포를 가진 데이터에 대해 균등한 분할을 보장하기 어렵다. 본 논문에서는 hB-tree 구조를 이용하여 균등한 분할을 보장하는 다차원 분할 기법을 제안하고 그 성능을 측정하기 위한 시뮬레이터 결과를 보인다. 시뮬레이션에서 hB-tree 분할 기법은 균등 분포뿐만 아니라 비균등 분포 데이터 집합에 대해서도 균등한 분할을 보인다.

B2V-Tree: An Indexing Scheme for Partial Match Queries on Wireless Data Streams (B2V-Tree: 무선 데이타 스트림에서 부분 부합 질의를 위한 색인 기법)

  • Chung, Yon-Dohn;Lee, Ji-Yeon
    • Journal of KIISE:Databases
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    • v.32 no.3
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    • pp.285-296
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    • 2005
  • In mobile distributed systems the data on the air can be accessed by a lot of mobile clients. And, we need an indexing scheme in order to energy-efficiently access the data on the wireless broadcast stream. In conventional indexing schemes, they use the values of primary key attributes and construct tree-structured index. Therefore, the conventional indexing schemes do not support content-based retrieval queries such as partial-match queries. In this paper we propose an indexing scheme, called B2V-Tree, which supports partial match queries on wireless broadcast data stream. For this purpose, we construct a tree-structured index which is composed of bit-vectors, where the bit-vectors are generated from data records through multi-attribute hashing.

Research on improving correctness of cardiac disorder data classifier by applying Best-First decision tree method (Best-First decision tree 기법을 적용한 심전도 데이터 분류기의 정확도 향상에 관한 연구)

  • Lee, Hyun-Ju;Shin, Dong-Kyoo;Park, Hee-Won;Kim, Soo-Han;Shin, Dong-Il
    • Journal of Internet Computing and Services
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    • v.12 no.6
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    • pp.63-71
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    • 2011
  • Cardiac disorder data are generally tested using the classifier and QRS-Complex and R-R interval which is used in this experiment are often extracted by ECG(Electrocardiogram) signals. The experimentation of ECG data with classifier is generally performed with SVM(Support Vector Machine) and MLP(Multilayer Perceptron) classifier, but this study experimented with Best-First Decision Tree(B-F Tree) derived from the Dicision Tree among Random Forest classifier algorithms to improve accuracy. To compare and analyze accuracy, experimentation of SVM, MLP, RBF(Radial Basic Function) Network and Decision Tree classifiers are performed and also compared the result of announced papers carried out under same interval and data. Comparing the accuracy of Random Forest classifier with above four ones, Random Forest is the best in accuracy. As though R-R interval was extracted using Band-pass filter in pre-processing of this experiment, in future, more filter study is needed to extract accurate interval.