• The KIPS Transactions:PartD
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• v.11D no.1
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• pp.11-22
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• 2004

As random access memory chip gets cheaper, it becomes affordable to realize main memory-based database systems. Consequently, reducing cache misses emerges as the most important issue in current main memory databases, in which CPU speeds have been increasing at 60% per year, compared to the memory speeds at 10% per you. In this paper, we design and implement a main-memory database system for real-time mobile GIS. Our system is composed of 5 modules： the interface manager provides the interface for PDA users； the memory data manager controls spatial and non-spatial data in main-memory using virtual memory techniques； the query manager processes spatial and non-spatial query : the index manager manages the MR-tree index for spatial data and the T-tree index for non-spatial index : the GIS server interface provides the interface with disk-based GIS. The MR-tree proposed propagates node splits upward only if one of the internal nodes on the insertion path has empty space. Thus, the internal nodes of the MR-tree are almost 100% full. Our experimental study shows that the two-dimensional MR-tree performs search up to 2.4 times faster than the ordinary R-tree. To use virtual memory techniques, the memory data manager uses page tables for spatial data, non- spatial data, T-tree and MR-tree. And, it uses indirect addressing techniques for fast reloading from disk.

• Journal of Korea Multimedia Society
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• v.11 no.11
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• pp.1601-1614
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• 2008

The number of web service users has been increased rapidly as existing services are changed into the web-based internet applications. Therefore, it is necessary for us to use web log pre-processing technique to detect attacks on diverse web service transactions and it is also possible to extract web mining information. However, existing mechanisms did not provide efficient pre-processing procedures for a huge volume of web log data. In this paper, we proposed both a field based parsing and a high-speed log indexing mechanism based on the suggested B-tree Index Vector structure for performance enhancement. In experiments, the proposed mechanism provides an efficient web log pre-processing and search functions with a session classification. Therefore it is useful to enhance web attack detection function.

• Journal of Korea Spatial Information System Society
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• v.7 no.2 s.14
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• pp.81-89
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• 2005

Declustering and parallel index structures are important research areas to improve a performance of databases. Previous researches proposed several distribution schemes for parallel R-trees, however there is no search schemes to be suitable for the index. In this paper, we propose schemes to improve the performance of range queries for distribute parallel indexes. The proposed schemes use the features that a parallel disk can read multiple nodes from various disks. The proposed schemes are verified using various implementations and performance evaluations. We propose new schemes which can read multiple nodes from multiple disks in contrast that to the previous schemes which can read a node from disk. The experimental evaluation shows that the proposed schemes give us the performance improvement by 40% from the previous researches.

• Journal of the Korean Association of Geographic Information Studies
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• v.8 no.1
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• pp.63-74
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• 2005

The telematics device, which is a typical embedded system on the transportation or vehicle, requires the embedded spatial DBMS based on RTOS (Real Time Operating System) for processing the huge spatial data in real time. This spatial DBMS can be developed very easily by SQL3 functions of the ORDBMS such as UDT (user-defined type) and UDF (user-defined function). However, developing index suitable for the embedded spatial DBMS is very difficult. This is due to the fact that there is no built-in SQL3 functions to construct spatial indexes. In this study, we compare and analyze both Generalized Search Tree and Relational Indexing methods which are suggested as common ways of developing User-Defined Indexes nowadays. Two implementations of R-Tree based on each method were done and region query performance test results were evaluated for suggesting a suitable indexing method of an embedded spatial DBMS, especially for telematics devices.

• Journal of KIISE:Databases
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• v.31 no.6
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• pp.624-640
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• 2004

Recently, with the rapid development of location-based techniques, index structures to efficiently manage moving objects have been required. In this paper, we propose a new spatio-temporal index structure that supports a future position retrieval and minimizes a update cost. The proposed index structure combines an assistant index structure that directly accesses current positions of moving objects with KDB-tree that is a space partitioning access method. The internal node in our proposed index structure keeps time parameters in order to support the future position retrieval and to minimize a update cost. Moreover, we propose new update and split methods to maximize the space utilization and the search performance. We perform various experiments to show that our proposed index structure outperforms the existing index structure.

• Journal of KIISE:Databases
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• v.32 no.5
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• pp.509-525
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• 2005

In this paper, we propose the index structure based on a vector approximation for efficiently supporting the similarity search of multi-dimensional data. The proposed index structure splits a region with the space partition method and allocates to the split region dynamic bits according to the distribution of data. Therefore, the index structure splits a region to the unoverlapped regions and can reduce the depth of the tree by storing the much region information of child nodes in a internal node. Our index structure represents the child node more exactly and provide the efficient search by representing the region information of the child node relatively using the region information of the parent node. We show that our proposed index structure is better than the existing index structure in various experiments. Experimental results show that our proposed index structure achieves about $40\%$ performance improvements on search performance over the existing method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.815-816
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• 2009

Owing to the development of computer technologies, to process data derived from various sensors is recently demanding. It is also increasing to demand the moving object based servies like the services of location based and mobile application services. That's why it is needed the processing of visualizing the services for education aspects. In this paper, we show the implemented results about $R^*$ tree algorithm to insert, delete and search a object in two dimension environment.

• Journal of Korea Spatial Information System Society
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• v.9 no.1
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• pp.1-13
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• 2007

The necessity of future index is increasing to predict the future location of moving objects promptly for various location-based services. A representative research topic related to future index is the probability trajectory prediction technique that improves reliability using the past trajectory information of moving objects in the road network environment. However, the prediction performance of this technique is lowered by the heavy load of extensive future trajectory search in long-range future queries, and its index maintenance cost is high due to the frequent update of future trajectory. Thus, this paper proposes the Probability Cell Trajectory-Tree (PCT-Tree), a cell-based future indexing technique for efficient long-range future location prediction. The PCT-Tree reduces the size of index by rebuilding the probability of extensive past trajectories in the unit of cell, and improves the prediction performance of long-range future queries. In addition, it predicts reliable future trajectories using information on past trajectories and, by doing so, minimizes the cost of communication resulting from errors in future trajectory prediction and the cost of index rebuilding for updating future trajectories. Through experiment, we proved the superiority of the PCT-Tree over existing indexing techniques in the performance of long-range future queries.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.7
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• pp.293-300
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• 2016

Traditional databases exploit a record-based model, where the attributes of a record are placed contiguously in a slow hard disk to achieve high performance. On the other hand, for read-intensive data analysis systems, the column-based compressed database has become a proper model because of its superior read performance. Currently, flash memory SSD is largely recognized as the preferred storage media for high-speed analysis systems. This paper introduces a compressed column-storage model and proposes a new index and its data management scheme for a high-capacity data warehouse system. The proposed index management scheme is based on the asymmetric index duplication and achieves superior search performance using the master index and compact index, particularly for large read-mostly databases. In addition, the data management scheme contributes to the read performance and high reliability by compressing the related columns and replicating them in two mirrored SSD. Based on the results of the performance evaluation under the high workload conditions, the data management scheme outperforms the traditional scheme in terms of the search throughput and response time.

• ETRI Journal
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• v.33 no.5
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• pp.741-751
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• 2011

This paper focuses on online speaker tracking for telephone conversations and broadcast news. Since the online applicability imposes some limitations on the tracking strategy, such as data insufficiency, a reliable approach should be applied to compensate for this shortage. In this framework, a set of reference speaker models are used as side information to facilitate online tracking. To improve the indexing accuracy, adaptation approaches in eigenvoice decomposition space are proposed in this paper. We believe that the eigenvoice adaptation techniques would help to embed the speaker space in the models and hence enrich the generality of the selected speaker models. Also, an index structure of the reference models is proposed to speed up the search in the model space. The proposed framework is evaluated on 2002 Rich Transcription Broadcast News and Conversational Telephone Speech corpus as well as a synthetic dataset. The indexing errors of the proposed framework on telephone conversations, broadcast news, and synthetic dataset are 8.77%, 9.36%, and 12.4%, respectively. Using the index tree structure approach, the run time of the proposed framework is improved by 22%.