• Proceedings of the Korea Contents Association Conference
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• 2018.05a
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• pp.537-538
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• 2018

이 논문에서는 CDP (Continuous Data Protection)에서 연속적인 데이터 보존 및 복원을 위한 파일시스템 변경 로그 레코드 색인 방법을 제안한다. 제안하는 파일시스템 변경 로그 레코드 색인 방법은 CDP에서 특정 시점의 파일들에 대한 복원 속도를 향상시키는 것이 목적이다. 제안하는 방법은 각 파일들을 논리적인 청크 (chunk) 단위로 나누고 각 청크에 대해서 일정 시간대별로 비트를 할당하여 파일의 변경을 추적하는 비트맵 (bitmap) 기반의 색인이다. 제안하는 비트맵 기반의 색인 방법은 멀티 레벨로 구성하여 비트맵 연산의 횟수를 줄일 수 있도록 한다. 이 논문에서는 제안하는 비트맵 기반의 색인 방법의 효율성을 입증하기 위해서 시뮬레이션을 수행한다.

• Journal of Internet Computing and Services
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• v.12 no.6
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• pp.43-51
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• 2011

The recent development of the technology for wireless mobile computing and applied technology for location-based services has made it possible to support query processing faster than that in the past. However, some technological limitations on hardware and software still exist. The most critical aspects of query processing are accuracy and speed. For improving the accuracy, it is required that detailed information on the data involved in query processing be saved. In this case, the amount of information on the data increases, which decreases the speed. On the other hand, for increasing the speed, it is necessary to reduce the broadcast cycle, which enables rapid data acquisition as desired. In this case, because of insufficient index information, the listen time for the client increases, which may cause unnecessary energy consumption. Therefore, a trade-off occurs between the accuracy and speed. This paper proposes a hierarchical bitmap-based spatial index (HBI) as a solution for the aforementioned problems. HBI describes an object with 0 and 1 on the Hilbert curve map. It reduces the broadcast cycle by decreasing the index size on the basis of bit information and tree structure. Therefore, it is able to shorten the listen time and query processing time. In addition, HBI enables the detection of the locations of all the objects so that it is possible selectively listen to a broadcast. A performance evaluation of the proposed technique demonstrates that it is excellent.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.2
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• pp.181-186
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• 2012

Recently there has been many active researches on searching similar sequences from data generated with the passage of time. Those data are classified as time series data or sequence data and have different semantics from scalar data of traditional databases. In this paper similar sequence search retrieves sequences that have a similar trend of value changes. At first we have transformed the original sequences by applying DFT. The converted data are more suitable for trend analysis and they require less number of attributes for sequence comparisons. In addition we have developed a region-based query and we applied bitmap indexes which could show better performance in data warehouse. We have built bitmap indexes with varying number of attributes and we have found the least cost query plans for efficient similar sequence searches.

• Journal of KIISE:Databases
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• v.32 no.4
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• pp.362-371
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• 2005

Similarity indexing and searching are well known to be difficult in high-dimensional applications such as multimedia databases. Especially, they become more difficult when multiple features have to be indexed together. In this paper, we propose a novel indexing method called the GB-index that is designed to efficiently handle complex similarity queries as well as relevance feedback in high-dimensional image databases. In order to provide the flexibility in controlling multiple features and query objects, the GB-index treats each dimension independently The efficiency of the GB-index is realized by specialized bitmap indexing that represents all objects in a database as a set of bitmaps. Main contributions of the GB-index are three-fold: (1) It provides a novel way to index high-dimensional data; (2) It efficiently handles complex similarity queries; and (3) Disjunctive queries driven by relevance feedback are efficiently treated. Empirical results demonstrate that the GB-index achieves great speedups over the sequential scan and the VA-file.

• Journal of the Korea Society of Computer and Information
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• v.17 no.1
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• pp.203-209
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• 2012

Recently, k-nearest neighbors query methods based on wireless broadcasting environment are actively studied. The advantage of wireless broadcasting environment is the scalability that enables collective query processing for unspecified users connected to the server. However, in case existing k-NN query is applied in wireless broadcasting environment, there can be a disadvantage that backtracking may occur and consequently the query processing time is increasing. In this paper proposes a hierarchical bitmap-based spatial index in order to efficiently process the k-NN queries in wireless broadcasting environment. HBI reduces the bitmap size using such bitmap information and tree structure. As a result, reducing the broadcast cycle can reduce the client's tuning time and query processing time. In addition, since the locations of all the objects can be detected using bitmap information, it is possible to tune to necessary data selectively. For this paper, a test was conducted implementing HBI to k-NN query and the proposed technique was proved to be excellent by a performance evaluation.

• Proceedings of the Korean Information Science Society Conference
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• 2007.06a
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• pp.19-20
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• 2007

• The KIPS Transactions:PartD
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• v.13D no.4 s.107
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• pp.455-462
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• 2006

Recently, the filtering approach using vector approximation such as VA-file[1] or LPC-file[2] have been proposed to support similarity search in high dimensional data space. This approach filters out many irrelevant vectors by calculating the approximate distance from a query vector using the compact approximations of vectors in database. Accordingly, the total elapsed time for similarity search is reduced because the disk I/O time is eliminated by reading the compact approximations instead of original vectors. However, the search time of the VA-file or LPC-file is not much lessened compared to the brute-force search because it requires a lot of computations for calculating the approximate distance. This paper proposes a new bitmap index structure in order to minimize the calculating time. To improve the calculating speed, a specific value of an object is saved in a bit pattern that shows a spatial position of the feature vector on a data space, and the calculation for a distance between objects is performed by the XOR bit calculation that is much faster than the real vector calculation. According to the experiment, the method that this paper suggests has shortened the total searching time to the extent of about one fourth of the sequential searching time, and to the utmost two times of the existing methods by shortening the great deal of calculating time, although this method has a longer data reading time compared to the existing vector approximation based approach. Consequently, it can be confirmed that we can improve even more the searching performance by shortening the calculating time for filtering of the existing vector approximation methods when the database speed is fast enough.

• Journal of Korea Multimedia Society
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• v.9 no.10
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• pp.1257-1265
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• 2006

As XML is increasingly used, the need of researches which are related with XML in various fields is also augmented. Many XML document management systems have been actively developed especially for the storage, processing and retrieval of XML documents. The BitCube is a three dimensional bitmap index system that could be manipulated efficiently and improves the performance of document retrieval. However, the site of index is increase rapidly, when a new bit is added to the axis. This problem is caused by its three dimensional memory structure with document, path and word. We suggest a path combining strategy of XML documents in this paper to solve the problem of BitCube that mentioned above. To reduce the size of index, our approach combines sibling nodes that has same ancestor paths, and transforms word axis into value axis. The method reduces the size of index, when the system com poses the three dimensional bitmap index. It also improves the speed of retrieving, and takes efficiency in storage space.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.1
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• pp.111-120
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• 2015

HDR(High dynamic range) imaging is a technique to represent a dynamic range of real world. Exposure fusion is a method to obtain a pseudo-HDR image and it directly fuses multi-exposure images instead of generating the true-HDR image. However, it results ghost artifacts while fusing the multi-exposure images with moving objects. To solve this drawback, temporal consistency assessment is proposed to remove moving objects. Firstly, multi-level threshold bitmap and brightness bitmap are proposed. In addition, hue-angle constancy map between multi-exposure images is proposed for compensating a bitmap. Then, two bitmaps are combined as a temporal weight map. Spatial domain image quality assessment is used to generate a spatial weight map. Finally, two weight maps are applied at each multi-exposure image and combined to get the pseudo-HDR image. In experiments, the proposed method reduces ghost artifacts more than previous methods. The quantitative ghost-free evaluation of the proposed method is also less than others.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07b
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• pp.46-48
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• 2005

기존의 다차원 색인 기법들이 고차원의 특징 벡터를 갖는 멀티미디어 컨텐츠 검색 분야에서 만족할 만한 성능을 보이지 못하므로, 이를 해결하기 위해 VA-File, LPC-File 등의 벡터 근사 방법이 개발 되었다. 이러한 방법들은 데이터의 접근에 소요되는 시간이 전체 검색시간의 대부분을 차지하는 경우에 효과적으로 사용할 수 있다. 그러나 고차원의 멀티미디어 데이터 검색에서 객체간의 거리 계산 시간은 데이터 접근 시간에 비해 무시할 만큼 작지 않으므로 이 방법들을 그대로 적용하기는 어렵다. 본 논문에서는 객체간의 거리 계산 시간을 줄이기 위한 새로운 색인 기법을 제안하고 실험을 통해 이 방법이 기존의 방법들에 비해 우수한 검색 성능을 가진다는 것을 보인다.