• Proceedings of the Korean Information Science Society Conference
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• 2006.10a
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• pp.511-515
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• 2006

집합이나 배열의 원소, 트리의 노드, 그래프의 정점과 간선 등과 같은 이산 객체는 일반적으로 주기억장치의 논리적 주소 값과 같은 정수로 표현되어 왔다. Succinct 표현은 이와 같은 n개의 이산 객체를 O(n) 비트에 표현하는 방법이다. 대부분의 succinct 표현은 rank와 select라는 함수를 기본적으로 사용하며, 다양한 연구들에 의해 현재 rank와 select 함수는 o(n)?? 비트만을 사용하여 ??O(1) 시간에 수행될 뿐만 아니라, 실제로도 실용적으로 구현되었다. 본 논문에서는 $n{\times}n$ 배열, 즉 2차원 비트 스트링에 대한 Rank 및 Select 함수를 새롭게 정의한다. 또한, $O(n^2log\;n)$ 비트를 사용하여 O(1) 시간에 Rank 질의를 수행하고 O(log n) 시간에 Select 질의를 수행하는 방법과, 보다 적은 $O(n^2)$ 비트를 사용하면서 O(log n) 시간에 Rank 질의를 수행하고 $O(log^2\;n)$ 시간에 Select 질의를 수행하는 방법을 제안한다. 본 논문에서 정의하는 2차원 배열 상의 Rank와 Select 함수는 이미 개발된 2차원 상의 써픽스 트리 등을 기반으로 향후 개발될 2차원 상의 압축된 인덱스 자료구조나 이미지 프로세싱 등에 유용하게 사용된다.

• Journal of KIISE:Information Networking
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• v.30 no.2
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• pp.282-292
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• 2003

This paper proposes an efficient data structure for forwarding IPv4 and IPv6 packets at the gigabit speed in backbone routers. The LPM(Longest Prefix Matching) search becomes a bottleneck of routers' performance since the LPM complexity grows in proportion to the forwarding table size and the address length. To speed up the forwarding process, this paper introduces a data structure named BMT(Bit-Map Tie) to minimize the frequent main memory accesses. All the necessary search computations in BMT are done over a small index table stored at cache. To build the small index table from the tie representation of the forwarding table, BMT represents a link pointer to the child node and a node pointer to the corresponding entry in the forwarding table with one bit respectively. To improve the poor performance of the conventional tries when their height becomes higher due to the increase of the address length, BMT adopts a binary search algorithm for determining the appropriate level of tries to start. The simulation experiments show that BMT compacts the IPv4 backbone routers' forwarding table into a small one less than 512-kbyte and achieves the average speed of 250ns/packet on Pentium II processors, which is almost the same performance as the fastest conventional lookup algorithms.

• Journal of KIISE:Software and Applications
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• v.36 no.9
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• pp.749-757
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• 2009

A Internet user can easily access to the target information by web searching using some key-words or categories in the present Internet environment. When some meta-data which represent attributes of several data structures well are used, then more accurate result which is matched with the intention of users can be provided. This study proposes a multiple dimensional vector tagging method for the small web user group who interest in maintaining and sharing the bookmark for common interesting topics. The proposed method uses vector tag method for increasing the effect of categorization, management, and retrieval of target information. The vector tag composes with two or more components of the user defined priority. The basic vector space is created time of information and reference value. The calculated vector value shows the usability of information and became the metric of ranking. The ranking accuracy of the proposed method compares with that of a simply link structure, The proposed method shows better results for corresponding the intention of users.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.2
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• pp.365-371
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• 2015

CB tree represents the binary trie by a compact binary sequence. However, retrieval time grows fast since the more keys stored in the trie, longer the binary sequences are. In addition it is inefficient for frequent key insertion/deletion. HCB tree is a hierarchical CB tree consisting of small binary tries. However it can not avoid shift operations and have to scan an additional table to refer child or parent trie. In order to improve retrieval performance and avoid shift operations when keys are inserted or deleted, we in this paper represent each separated trie by a full binary trie and then assign the unique identifier to it. Finally the theoretical evaluations show that both the proposed approach and HCB tree provides better than CB tree for key retrieval. The proposed approach shows the highest performance in case of key insertion/deletion and moreover requires only 71%~89% of storage as compared with CB tree.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.5_6
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• pp.268-278
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• 2004

In this paper, we describe our experience in the design and implementation of the SMART file system to handle multimedia workload. Our work has three design objectives: (ⅰ) efficient support for sequential workload, (ⅱ) avoiding disk fragmentation, (ⅲ) logical unit based file access. To achieve these three objectives, we develop a file system where a file consists of linked list of Data Unit Group. Instead of tree like structure of the legacy Unix file system, we use single level file structure. Our file system can also access the file based upon the logical unit which can be video frame or audio samples. Data Unit Group is a group of logical data units which is allocated continuous disk blocks. At the beginning of each Data Unit Group, there exists an index array. Each index points to the beginning of logical data units, e.g. frames in the Data Unit Group. This index array enables the random access and sequencial access of semantic data units. SMART file system is elaborately tailored to effectively support multimedia workload. We perform physical experiments and compare the performance of SMART file system with EXT2 file system and SGI XFS file system. In this experiment, SMART file system exhibits superior performance under streaming workload.

• Journal of KIISE:Computer Systems and Theory
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• v.32 no.5
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• pp.255-259
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• 2005

To search a pattern P in a text, such index data structures as suffix trees and suffix arrays are widely used in diverse applications of string processing and computational biology. It is well known that searching in suffix trees is faster than suffix ways in the aspect of time complexity, i.e., it takes O(${\mid}P{\mid}$) time to search P on a constant-size alphabet in a suffix tree while it takes O(${\mid}P{\mid}+logn$) time in a suffix way where n is the length of the text. In this paper we present a linear-tim8 search algorithm in suffix arrays for constant-size alphabets. For a gene.al alphabet $\Sigma$, it takes O(${\mid}P{\mid}log{\mid}{\Sigma}{\mid}$) time.