• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.8
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• pp.1843-1850
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• 2004

If the location information of a great number of cars kept for business with telematics terminals is acquired and managed efficiently, this information forms the foundation for controlling cars and traffic flows. The studies on the pure spatial indices have focused on the efficient retrievals. However, the acquisition and management of the terminal location of moving objects are more important than the efficiency of the query processing in the moving object databases. Therefore, it will be need to adopt parallel processing system for the moving object databases which should maintain the object's current location as precise as possible. This paper proposes a location management system using CDMA communications of telematics terminals. More precisely, we propose a architecture of spatial indexing mobile objects using multiple processors, and also newly propose a method of splitting buckets using the properties of moving objects in order to minimize the number of database updates. We also propose a acquisition method for gathering the location information of moving objects and passing the information of the bucket extents in order to reduce the amount of passed messages between processors.

• Journal of KIISE:Databases
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• v.35 no.2
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• pp.169-181
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• 2008

Because moving objects usually move on spatial networks, efficient trajectory index structures are required to achieve good retrieval performance on their trajectories. However, there has been little research on trajectory index structures for spatial networks such as FNR-tree and MON-tree. But, because FNR-tree and MON-tree are stored by the unit of the moving object's segment, they can't support the whole moving objects' trajectory. In this paper, we propose an efficient trajectory index structure, named Trajectory of Moving objects on Network Tree(TMN Tree), for moving objects. For this, we divide moving object data into spatial and temporal attribute, and preserve moving objects' trajectory. Then, we design index structure which supports not only range query but trajectory query. In addition, we divide user queries into spatio-temporal area based trajectory query, similar-trajectory query, and k-nearest neighbor query. We propose query processing algorithms to support them. Finally, we show that our trajectory index structure outperforms existing tree structures like FNR-Tree and MON-Tree.

• Journal of KIISE:Databases
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• v.30 no.1
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• pp.52-63
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• 2003

Spatiotemporal moving objects are changing their Positions and/or shape over time in real world. As most of the indices of moving object are based on the R-tree. they have defects of the R-tree which are dead space and overlap. Some of the indices amplify the defects of the R-tree. In the paper, to solve the problems, we propose the MPR-tree(Moving Point R-tree) using Projection operation which has more effective search than existing moving point indices on time slice query and spatiotemporal range query. The MPR-tree connects positions of the same moving objects over time by using linked list, so it processes the combined query about trajectory effectively. The usefulness of the Projection operation is confirmed during processing moving object queries and in practical use of space from experimentation to compare MPR-tree with existing indices of moving objects. The proposed MPR-tree would be useful in the LBS, the car management using GPS, and the navigation system.

• Proceedings of the Korean Information Science Society Conference
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• 2002.04b
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• pp.124-126
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• 2002

본 논문에서는 비디오 데이터가 지니는 이동 객체의 움직임 궤적(moving objects'trajectories)에 대해 유사 부분 움직임 궤적 검색을 효율적으로 지원하는 N-워핑(N-warping) 알고리즘을 제안한다. 제안하는 알고리즘은 기존의 시계열 데이터베이스에서 유사 서브시퀸스 검색을 위해 사용되었던 타임 워핑 변환 기법(time-warping transformation)을 변형란 알고리즘이다. 또한 제안하는 알고리즘은 움직임 궤적을 모델링하기 위해 사용되는 단일 속성(property)인 각도뿐만 아니라, 거리와 시간과 같은 다중 속성을 지원하며, 사용자 질의에 대해 유사 부분 움직임 궤적 검색을 가능하게 하는 근사 매칭(approximate matching)을 지원한다

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.6
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• pp.1266-1272
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• 2004

Location-Based Services(LBS) give rise to location-dependent queries of which results depend on the positions of moving objects. Because positions of moving objects change continuously, indexes of moving object must perform update operations frequently for keeping the changed position information. Existing spatial index (Grid File, R-Tree, KDB-tree etc.) proposed as index structure to search static data effectively. There are not suitable for index technique of moving object database that position data is changed continuously. In this paper, I propose a dynamic hashing index that insertion/delete costs are low. The dynamic hashing structure is that apply dynamic hashing techniques to combine a hash and a tree to a spatial index. The results of my extensive experiments show the dynamic hashing index outperforms the $R^$ $R^*$-tree and the fixed grid.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.95-104
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• 2022

A TPR-tree is a well-known indexing structure that is developed to answer queries about the current or future time locations of moving objects. For the purpose of space efficiency, the TPR-tree employs the notion of VBR (velocity bounding rectangle)so that a regionalrectangle presents varying positions of a group of moving objects. Since the rectangle computed from a VBR always encloses the possible maximum range of an indexed object group, a search process only has to follow VBR-based rectangles overlapped with a given query range, while searching toward candidate leaf nodes. Although the TPR-tree index shows up its space efficiency, it easily suffers from the problem of dead space that results from fast and constant expansions of VBR-based rectangles. Against this, the TPR-tree index is enforced to update leaf nodes for reducing dead spaces within them. Such an update-prone feature of the TPR-tree becomes more problematic when the tree is saved in flash storage. This is because flash storage has very expensive update costs. To solve this problem, we propose a new Bloom filter based caching scheme that is useful for reducing updates in a flash TPR-tree. Since the proposed scheme can efficiently control the frequency of updates on a leaf node, it can offer good performance for indexing moving objects in modern flash storage.

• Journal of KIISE:Databases
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• v.29 no.6
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• pp.441-452
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• 2002

If continuous moving objects are managed by conventional database, it is not possible for them to store all position information changed over time in the database. Therefore, a time period of regular rate is determined and position information of moving objects are discretely stored in the system for every time period. However, if continuous moving objects are managed as discrete model, we will have problems which cannot properly answer to the query about uncertain past or future position information. To solve this problem, in this paper, we propose the method and algorithm which use the history information stored in the same database, to estimate the past or future location of moving objects. The cubic spline interpolation is used to estimate the past location and the mean movement value of the history information is used to predict the future location of moving objects. Finally, from the location estimation experimentation of using virtual trajectory and location sample, we proved that the proposed cubic spline function has less error than the linear function.

• The KIPS Transactions:PartD
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• v.12D no.1 s.97
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• pp.43-50
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• 2005

The Processing domains of spatio-temporal databases are divided into time-series databases for moving objects and sequence databases for discrete historical objects. Recently the selectivity estimation techniques for query optimization in spatio-temporal databases have been studied, but focused on query optimization in time-series databases. There wat no previous work on the selectivity estimation techniques for sequence databates as well. Therefore, we construct T-Minskew histogram for query optimization In sequence databases and propose a selectivity estimation method using the T-Minskew histogram. Furthermore we propose an effective histogram maintenance technique for food performance of the histogram.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.4
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• pp.59-66
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• 2016

For the performance experiments of databases systems with moving object databases, we need moving object trajectory data sets. For example, benchmark data sets of moving object trajectories are required for experiments on query processing of moving object databases. For those reasons, several tools have been developed for generating moving objects in Euclidean spaces or road network spaces. Indoor space differs from outdoor spaces in many aspects and moving object generator for indoor space should reflect these differences. Even some tools were developed to produce virtual moving object trajectories in indoor space, the movements generated by them are not realistic. In this paper, we present a moving object generation tool for indoor space. First, this tool generates trajectories for pedestrians in an indoor space. And it provides a parametric generation of trajectories considering not only speed, number of pedestrians, minimum distance between pedestrians but also type of spaces, time constraints, and type of pedestrians. We try to reflect the patterns of pedestrians in indoor space as realistic as possible. For the reason of interoperability, several geospatial standards are used in the development of the tool.

• 한국공간정보시스템학회:학술대회논문집
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• 2004.12a
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• pp.113-116
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• 2004

Assisted by high technologies of information and communication in storing and collecting moving object information, many applications have been developing technical methods to exploit databases of moving objects effectively and variously. Among them, today, Current and Anticipated Future Position Indexing methods manage current positions of moving objects in order to anticipate future positions of them or more complex future queries. They, however, strongly demand update performance as fast enough to guarantee certainty of queries as possible. In this paper, we propose a new indexing mettled derived from the TPR-tree that should has update performance considerably improved, we named it BUR-tree. In our method, index structure can be inserted, deleted, and updated with a number (or bulk) of objects simultaneously rather than one object at a time as in conventional methods. This method is intended to be applied to a traffic network in which vast number of objects, such as cars, pedestrians, moves continuously.