• Journal of the Korea Convergence Society
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• v.10 no.4
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• pp.33-38
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• 2019

Recently, to support location-based services, there have been many researches which consider the spatial network. For this, there are many experimental data for data processing on the road network. However, the data to process the trajectory of moving objects are not suitable. Therefore, we propose index structure to process the trajectory data on the road network and the trajectory data generation algorithm. In addition, to prove efficiency of our index structure and algorithm, we show that edge-based trajectory data are generated through the proposed algorithm using the map data of San Francisco Bay.

• The Journal of the Korea Contents Association
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• v.7 no.7
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• pp.11-23
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• 2007

Applications involving moving objects require index structures to handle frequent updates of objects' locations efficiently. Several methods to index the current, the past and the future positions of moving objects have been proposed for the applications. Most of them are based on R-tree like index structures. Some researches have made efforts to improve update performance of R-trees that are actually focused on query performance. Even though the update performance is improved by researchers' efforts, the overhead and immaturity of concurrency control algorithms of R-trees makes us hesitate to choose them for moving objects. In this paper, we propose an update efficient indexing method that can be applicable for indexing the past, the current and the future locations. The proposed index is based on B+-Trees and Hilbert curve. We present an advanced Hilbert curve that adjusts automatically the order of Hilbert curve in subregions according to the data distribution and the number of data objects. Through empirical studies, we show that our strategy achieves higher response time and throughput.

• Journal of Korea Spatial Information System Society
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• v.6 no.2 s.12
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• pp.3-13
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• 2004

The TPR-tree exploits bounding rectangles based on the function of time in order to index moving objects. As time passes on, each edge of a BR expands with the fastest velocity vector. Since the expansion of the BR results in a serious overlaps between neighboring nodes, the performance of range query is getting worse. In this paper, we propose schemes to reorganize bounding rectangles of nodes. When inserting a moving object, we exploit a forced merging scheme to merge two overlapped nodes and re-split it. When deleting a moving object, we used forced reinsertion schemes to reinsert other objects of a node into a tree. The forced reinsertion schemes are classified into a deleted node reinsertion scheme and an overlapped nodes reinsertion scheme. The overlapped nodes reinsertion scheme outperforms the forced merging scheme and the deleted node reinsertion scheme in all experiments.

• 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 Internet Computing and Services
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• v.5 no.4
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• pp.77-94
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• 2004

Recently, the needs of index structure which manages moving objects efficiently have been increased because of the rapid development of location-based techniques. Existing index structures frequently need updates because moving objects change continuatively their positions. That caused entire performance loss of the index structures. In this paper, we propose a new index structure called the TPKDB-tree that is a spatio-temporal index structure based on KDB-tree. Our technique optimizes update costs and reduces a search time for moving objects and reduces unnecessary updates by expressing moving objects as linear functions. Thus, the TPKDB-tree efficiently supports the searches of future positions of moving objects by considering the changes of moving objects included in the node as time-parameter. To maximize space utilization, we propose the new update and split methods. Finally, we perform various experiments to show that our approach outperforms others.

• Journal of KIISE:Databases
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• v.33 no.4
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• pp.396-408
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• 2006

Moving object databases manage a large amount of past location data which are accumulated as the time goes. To retrieve fast the past location of moving objects, we need index structures which consider features of moving objects. The KDB-tree has a good performance in processing range queries. Although we use the KDB-tree as an index structure for moving object databases, there has an over-split problem in the spatial domain since the feature of moving object databases is to increase the time domain. Because the over-split problem reduces spatial regions in the MBR of nodes inverse proportion to the number of splits, there has a problem that the cost for processing spatial-temporal range queries is increased. In this paper, we propose the dynamic split strategy of the KDB-tree to process efficiently the spatial-temporal range queries. The dynamic split strategy uses the space priority splitting method for choosing the split domain, the recent time splitting policy for splitting a point page to maximize the space utilization, and the last division policy for splitting a region page. We compare the performance of proposed dynamic split strategy with the 3DR-tree, the MV3R-tree, and the KDB-tree. In our performance study for range queries, the number of node access in the MKDB-tree is average 30% less than compared index structures.

• The KIPS Transactions:PartD
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• v.13D no.4 s.107
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• pp.477-490
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• 2006

Existing index structures need very much update cost because they repeat delete and insert operations in order to update continuously moving objects. In this paper, we propose a new index structure which reduces the update cost of continuously moving objects. The proposed index structure consists of a space partitioning index structure that stores the location of the moving objects and an auxiliary index structure that directly accesses to their current positions. In order to increase the fanout of the node, it stores not the real partitioning area but kd-tree as the information about the child node of the node. In addition, we don't traverse a whole index structure, but access the leaf nodes directly and accomplish a bottom-up update strategy for efficiently updating the positions of moving objects. We show through the various experiments that our index structure outperforms the existing index structures in terms of insertion, update and retrieval.

• Journal of KIISE
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• v.43 no.5
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• pp.590-595
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• 2016

In this study, we propose an efficient method for monitoring continuous top-k queries. In contrast to the conventional top-k queries, the presented top-k query considers both spatial and non-spatial attributes. We proposed a novel main-memory based grid access method, called Bit-Vector Grid Index (BVGI). The proposed method quickly identifies whether the moving objects are included in some of the grid cell by encoding a non-spatial attribute value of the moving object to bit-vector. Experimental simulations demonstrate that the proposed method is several times faster than the previous method and uses considerably less memory.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.2
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• pp.364-370
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• 2014

The management and analysis of spatio-temporal and multimedia data is a hot issue in database research because such data types are handled in manny applications. Querying databases of such a content is very important for these applications. This paper addresses algorithms that make index structure by using Douglas-Peucker Algorithm and process range query efficiently on moving objects trajectories. We compare and analyze our algorithms and MBR by experiments. Our algorithms make smaller size of index structure and process more efficiently.

• Journal of Korea Spatial Information System Society
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• v.10 no.3
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• pp.67-78
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• 2008

With the rapid development of wireless communication and mobile equipment, many applications for location-based services have been emerging. Moving objects such as vehicles and ships change their positions over time. Moving objects have their moving path, called the trajectory, because they move continuously. To monitor the trajectory of moving objects in a large scale database system, an efficient Indexing scheme to processed queries related to trajectories is required. In this paper, we focus on the issues of minimizing the dead space of index structures. The Minimum Bounding Boxes (MBBs) of non-leaf nodes in trajectory-preserving indexing schemes have large amounts of dead space since trajectory preservation is achieved at the sacrifice of the spatial locality of trajectories. In this thesis, we propose entry relocating techniques to reduce dead space and overlaps in non-leaf nodes. we present performance studies that compare the proposed index schemes with the TB-tree and the R*-tree under a varying set of spatio-temporal queries.