• Journal of KIISE:Databases
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• v.28 no.1
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• pp.69-85
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• 2001

공간 데이터베이스에서 효율적으로 공간 질의를 처리하기 위해서는 클러스터링을 통해서 이스크 접근 비용을 줄이는 것이 필요하다. 이 논문은 공간 지역성에 기반을 둔 여러 가지 클러스터링 알고리즘을 제안하고 실험을 통해 제안한 클러스터링 알고리즘의 성능을 평가하였다. 이 논문에서 제안하는 클러스터링 알고리즘은 객체 클러스터링 알고리즘과 셀 클러스터링 알고리즘으로 나뉜다. 객체 클러스터링 알고리즘은 정규 준할 공간 색인 구조에서 영역 분할 선과 겹치는 객체들의 저장 위치를 결정하는데 사용된다. 셀 클러스터링 알고리즘은 클러스터를 만들기 위해 정규 분할된 영역들을 그룹화하는데 사용된다. 실험결과 객체 클러스터링 알고리즘에서는 객체간의 거리를 이용한 경우에 대체로 좋은 성능을 보였지만, 버퍼 크기가 커지거나 데이터가 희박한 영역의 질의에 있어서는 알고리즘 별로 성능의 차이는 거의 없었다. 셀 클러스터링 알고리즘에 대한 실험에서는 이 논문에서 제안한 클러스터링 알고리즘은 N-순서화 기법에 의한 클러스터링 알고리즘에 비해 우수한 성능을 보였다. 특히 중복 참조도를 이용한 경우와 셀의 무게 중심간 거리를 이용한 방법이 가장 우수하였다.

• Journal of KIISE:Databases
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• v.28 no.1
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• pp.95-103
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• 2001

본 논문에서는 분산된 준구조적 데이터에 대한 질의 처리 문제를 다룬다. 분산된 준구조적 데이터는 루트가 있고 간선에 레이블이 있는 그래프 모델로 표현될 수 있으며, 그래프의 조드들은 한 사이트 또는 여러 사이트들에 위치할 수 있다. 분산된 준구조적 데이터의 효율적인 검색을 위해 ‘질의 단축 및 확산’ 방법에 기반을 둔 질의 처리 모델을 제안한다. 이 방법은 사용자 질의가 사이트 내부에서 단축되고 다른 사이트로 분산되는 과정을 통해 데이터를 검색한다. 또한, 제안된 모델에 필요한 알고리즘들을 제시하고 정확성을 증명한다.

• Information and Communications Magazine
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• v.23 no.10
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• pp.53-62
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• 2006

다양한 유무선 액세스망들이 IP기반 공통의 코어망을 이용할 수 있도록 연동되는 BcN에서는 휴대단말이 이종망간에 이동하는 상황에서도 끊김 없는 서비스를 제공하는 것이 필수 요소 기술이고, 이를 지원 하기 위해서 고속의 핸드오버 기능 및 위치 관리 기능이 필요로 된다. 특히 고속의 핸드오버를 수행하기 위해서는 액세스망에 의존적인 데이타링크 계층 기능들과 IP기반 이동성 기능들이 밀접히 연계되어 동작되어야 한다. 본 고에서는 IP망에서의 대표적인 이동성 지원 방법인 Mobile IP 기술과 데이터링크 계층의 이동성 관련 트리거 정보를 통일돈 형태로 상위 계층으로 전달하는 IEEE 802.21 MIH(Media Independent Hanover) 기술에 대해 소개하고 Mobile IP와 MIH기술을 바탕으로 이종망간에 끊김없는 이동성을 제공하는 방법에 대해서 살펴볼 것이다.

• Journal of KIISE:Databases
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• v.36 no.3
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• pp.198-214
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• 2009

Trajectories of RFID tags can be modeled as a line, denoted by tag interval, captured by an RFID reader and indexed in a three-dimensional domain, with the axes being the tag identifier (TID), the location identifier (LID), and the time (TIME). Distribution of tag intervals in the domain space is an important factor for efficient processing of a query for tracing tags and is changed according to arranging coordinates of each domain. Particularly, the arrangement of LIDs in the domain has an effect on the performance of queries retrieving the traces of tags as times goes by because it provides the location information of tags. Therefore, it is necessary to determine the optimal ordering of LIDs in order to perform queries efficiently for retrieving tag intervals from the index. To do this, we propose LID proximity for reordering previously assigned LIDs to new LIDs and define the LID proximity function for storing tag intervals accessed together closely in index nodes when a query is processed. To determine the sequence of LIDs in the domain, we also propose a reordering scheme of LIDs based on LID proximity. Our experiments show that the proposed reordering scheme considerably improves the performance of Queries for tracing tag locations comparing with the previous method of assigning LIDs.

• Journal of KIISE:Databases
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• v.35 no.1
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• pp.84-95
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• 2008

Wireless sensor networks have recently emerged as a platform for several applications. By deploying wireless sensor nodes and constructing a sensor network, we can remotely obtain information about the behavior, conditions, and positions of objects in a region. Since sensor nodes operate on batteries, energy-efficient mechanisms for gathering sensor data are indispensable to prolong the lifetime of a sensor network as long as possible. In this paper, we propose a novel clustering algorithm that distributes the energy consumption of a cluster head. First, we analyze the energy consumption if cluster heads and divide each cluster into a collection layer and a transmission layer according to their roles. Then, we elect a cluster head for each layer to distribute the energy consumption of single cluster head. In order to show the superiority of our clustering algorithm, we compare it with the existing clustering algorithm in terms of the lifetime of the sensor network. As a result, our experimental results show that the proposed clustering algorithm achieves about $10%{\sim}40%$ performance improvements over the existing clustering algorithms.

• Journal of KIISE:Information Networking
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• v.33 no.1
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• pp.91-102
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• 2006

We analyze the performance of MAC-layer Reed-Solomon error recovery in the cdma2000 1xEV-DO Broadcast and Multicast Services (BCMCSs) environment, with respect to the size of the ECB (Error Control Block) and the air-channel condition, and establish the relationship between ECB size, error recovery capacity and service latency. From this we propose an adaptive error recovery scheme which adjusts the size of the ECB to reflect the environment of the mobile nodes so as to meet the required service quality (target bit error-rate), while reducing the latency of real-time applications. Extensive simulation results show the effectiveness of our approach compared to the current static scheme. Proposed adaptive schemes achieves near optimal solution with respect to service latency while satisfying the required service quality.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.11 no.2
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• pp.79-87
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• 1993

Executing various constructions and national land planning, it has rised importance how to acquire 3-dimensional geographical information efficiently. In conjunction with this, the concerned parties are interested in the accuracy of GPS positioning and applications. This study suggest the efficiency and possibility to apply geographical information construction by kinematic GPS surveying as comparing kinematic GPS results with triangulation, trilateration and static GPS results. In this study, we try to compare static with kinematic and can determine 3-D positions with difference of 6 mm in distance, 2"/10,000-4"/10,000, 20 cm in latitude, longitude and height at local area. In addition, difference from conventional surveying is about 1"/l0,000-3"/10,000 in horizontal. Therefore it is expected to apply kinematic GPS to make out topographic map and to construct data base associated with GIS.associated with GIS.

• Journal of KIISE:Software and Applications
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• v.32 no.5
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• pp.385-395
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• 2005

Long sentence analysis has been a critical problem in machine translation because of high complexity. The methods of intra-sentence segmentation have been proposed to reduce parsing complexity. This paper presents the intra-sentence segmentation method based on maximum entropy probability model to increase the coverage and accuracy of the segmentation. We construct the rules for choosing candidate segmentation positions by a teaming method using the lexical context of the words tagged as segmentation position. We also generate the model that gives probability value to each candidate segmentation positions. The lexical contexts are extracted from the corpus tagged with segmentation positions and are incorporated into the probability model. We construct training data using the sentences from Wall Street Journal and experiment the intra-sentence segmentation on the sentences from four different domains. The experiments show about $88\%$ accuracy and about $98\%$ coverage of the segmentation. Also, the proposed method results in parsing efficiency improvement by 4.8 times in speed and 3.6 times in space.

• Journal of KIISE:Databases
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• v.33 no.1
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• pp.12-31
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• 2006

The n-gram inverted index has two major advantages: language-neutral and error-tolerant. Due to these advantages, it has been widely used in information retrieval or in similar sequence matching for DNA and Protein databases. Nevertheless, the n-gram inverted index also has drawbacks: the size tends to be very large, and the performance of queries tends to be bad. In this paper, we propose the two-level n-gram inverted index (simply, the n-gram/2L index) that significantly reduces the size and improves the query performance while preserving the advantages of the n-gram inverted index. The proposed index eliminates the redundancy of the position information that exists in the n-gram inverted index. The proposed index is constructed in two steps: 1) extracting subsequences of length m from documents and 2) extracting n-grams from those subsequences. We formally prove that this two-step construction is identical to the relational normalization process that removes the redundancy caused by a non-trivial multivalued dependency. The n-gram/2L index has excellent properties: 1) it significantly reduces the size and improves the Performance compared with the n-gram inverted index with these improvements becoming more marked as the database size gets larger; 2) the query processing time increases only very slightly as the query length gets longer. Experimental results using databases of 1 GBytes show that the size of the n-gram/2L index is reduced by up to 1.9${\~}$2.7 times and, at the same time, the query performance is improved by up to 13.1 times compared with those of the n-gram inverted index.

• Journal of Korea Spatial Information System Society
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• v.6 no.2 s.12
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• pp.51-62
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• 2004

Recently, the location-based service for moving customers is becoming one of the most important service in mobile communication area. For moving object applications, there are lots of update operations and such update loads are concentrated on some particular area unevenly. The primary processing of LBS application is spatio-temporal range queries. To improve the throughput of spatio-temporal range queries, the time of disk I/O in query processing should be reduced. In this paper, we adopt non-uniform two-level grid index structures of GALIS architecture,which are designed to minimize update operations. We propose query scheduling technique using spatial relationship and time relationship and a combined spatio-temporal query processing method using time zone concepts to improve the throughput of query processing. Some experimental results are shown for range queries with different query range to show the performance tradeoffs of the proposed methods.