• The KIPS Transactions:PartD
• /
• v.12D no.4 s.100
• /
• pp.507-520
• /
• 2005

The R-trees are usually used for an index of trajectories in moving-objects databases. However, they need to access a number of nodes to trace same trajectories because of considering only a spatial proximity. Overlaps and dead spaces should be minimized to enhance the performance of range queries in moving-objects indexes. Trajectories of moving-objects should be preserved to enhance the performance of the trajectory queries. In this paper, we propose the TP3DR-tree(Trajectory Preserved 3DR-tree) using clusters of trajectories for range and trajectory queries. The TP3DR-tree uses two split policies: one is a spatial splitting that splits the same trajectory by clustering and the other is a time splitting that increases space utilization. In addition, we use connecting information in non-leaf nodes to enhance the performance of combined-queries. Our experiments show that the new index outperforms the others in processing queries on various datasets.

• Journal of Korea Spatial Information System Society
• /
• v.8 no.1 s.16
• /
• pp.37-57
• /
• 2006

To support Location Based Services, the technology to store and search locations information of moving objects effectively was needed. And the study about indexes to manage these moving objects effectively has been done. As these indexes for moving objects was not considered for the objects which are moving along constrained networks such as road and railroad, indexes for the moving objects based on constrained networks was proposed. But these kinds of indexes have two problems as following. First, as the indexes for the moving objects based on constrained networks is divided according to time domain, when the places of moving objects from the present to the past are needed, the problem to search past indexes as well as present indexes occurs. Second, in this case, we should construct both present indexes and past indexes, so we have no other choice but to spend space cost and reconstruction cost additionally. This paper proposes A Unified Index for Moving Objects in Constrained Networks to solve these kinds of problems. As this proposed indexes support both present location and past location of moving objects, it can solve the current problems such as when we search present and past location of moving objects, we need a separate processing procedure. And as it consolidated the common parts of current location indexes and past location indexes, we can use less space cost and reconstruction cost than when we maintain indexes separately.

• Convergence Security Journal
• /
• v.8 no.4
• /
• pp.97-104
• /
• 2008

Recently, the wireless positioning techniques and mobile computing techniques have rapidly developed to use location data of moving objects. The more the number of moving objects is numerous and the more periodical sampling of locations is frequent, the more location data of moving objects become very large. Hence the system should be able to efficiently manage mass location data, support various spatio-temporal queries for LBS, and solve the uncertainty problem of moving objects. Therefore, in this paper, innovating the location data of moving object effectively, we propose Rend 3DR-tree method to decrease the dead space and complement the overlapping of nodes by utilizing 3DR-tree with the indexing structure to support indexing of current data and history data.

• Journal of KIISE:Databases
• /
• v.35 no.5
• /
• pp.447-458
• /
• 2008

In this paper, we address an efficient processing scheme for k-nearest neighbor queries to retrieve k static objects in road network databases. Existing methods cannot expect a query processing speed-up by index structures in road network databases, since it is impossible to build an index by the network distance, which cannot meet the triangular inequality requirement, essential for index creation, but only possible in a totally ordered set. Thus, these previous methods suffer from a serious performance degradation in query processing. Another method using pre-computed network distances also suffers from a serious storage overhead to maintain a huge amount of pre-computed network distances. To solve these performance and storage problems at the same time, this paper proposes a novel approach that creates an index for moving objects by approximating their network distances and efficiently processes k-nearest neighbor queries by means of the approximate index. For this approach, we proposed a systematic way of mapping each moving object on a road network into the corresponding absolute position in the m-dimensional space. To meet the triangular inequality this paper proposes a new notion of average network distance, and uses FastMap to map moving objects to their corresponding points in the m-dimensional space. After then, we present an approximate indexing algorithm to build an R*-tree, a multidimensional index, on the m-dimensional points of moving objects. The proposed scheme presents a query processing algorithm capable of efficiently evaluating k-nearest neighbor queries by finding k-nearest points (i.e., k-nearest moving objects) from the m-dimensional index. Finally, a variety of extensive experiments verifies the performance enhancement of the proposed approach by performing especially for the real-life road network databases.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2014.10a
• /
• pp.418-421
• /
• 2014

Because of the rapid growth of mobile communication and wireless communication, Location-based services are handled in many applications. So, the management and analysis of spatio-temporal data are a hot issue in database research. Index structure and query processing of such contents are very important for these applications. This paper addressees algorithms that make index structure by using Douglas-Peucker Algorithm and process nearest neighbor search query efficiently on moving objects trajectories. We compare and analyze our algorithms by experiments. Our algorithms make small size of index structure and process the query more efficiently.

• Journal of Korea Spatial Information System Society
• /
• v.7 no.1 s.13
• /
• pp.13-24
• /
• 2005

Objects, which change their positions over time such as cars, are called moving objects. Trajectories of a moving object have large volumes because trajectories are accumulated. Efficient indexing techniques for searching these large volumes of trajectories are needed in the moving object databases. Especially the TB-tree which supports bundling trajectories is suitable for processing combined queries which have 2 steps: first step is selecting trajectories (range search), next is selecting the parts of each trajectory (trajectory search). But the TB-tree has unnecessary disk accesses cause of lack of spatial discrimination in range queries. In this paper, we propose and implement the splitting polity which can reduce dead spaces of non-leaf node in order to process range queries efficiently. The policy has better performance about range queries than the TB-tree as well as the advantages of the TB-tree, such as highly space utilization and efficient trajectory extraction. This paper shows that the newly proposed split policy has better performance in processing the range queries than that of the TB-tree by experimental evaluation.

• Journal of KIISE:Databases
• /
• v.35 no.5
• /
• pp.432-446
• /
• 2008

Queries for tracing tag locations are among the most challenging requirements in RFID based applications, including automated manufacturing, inventory tracking and supply chain management. For efficient query processing, a previous study proposed the index scheme for storing tag objects, based on the moving object index, in 3-dimensional domain with the axes being the tag identifier, the reader identifier, and the time. In a different way of a moving object index, the ranges of coordinates for each domain are quite different so that the distribution of query regions is skewed to the reader identifier domain. Previous indexes for tags, however, do not consider the skewed distribution for query regions. This results in producing many overlaps between index nodes and query regions and then causes the problem of traversing many index nodes. To solve this problem, we propose a new disproportional insertion and split policy of the index for RFID tags which is based on the R*-tree. For efficient insertion of tag data, our method derives the weighted margin for each node by using weights of each axis and margin of nodes. Based the weighted margin, we can choose the subtree and the split method in order to insert tag data with the minimum cost. Proposed insertion method also reduces the cost of region query by reducing overlapped area of query region and MBRs. Our experiments show that the index based on the proposed insertion and split method considerably improves the performance of queries than the index based on the previous methods.

• Journal of Korea Spatial Information System Society
• /
• v.9 no.1
• /
• pp.31-43
• /
• 2007

Sensor data have the characteristics such as numerous and continuous data. Therefore, it is required to develop an index which could retrieve a specific sensor data efficiently from numerous sensed data. The index should have an efficient delete operation for the past data to support the data archiving. In this paper, we have proposed and implemented an index splitting technique to support the sensor data archiving. These splitted indexes compose of a virtual index (that is, index management component), which is shown as single tree from outside. Experimental results show that in the case of 100,000 insert operations the splitted index performs 8% better than the traditional TB-tree maximumly. And the splitted index outperforms TB-tree with retrieving queries when the region of query is small and the size of time domain is large.

• Proceedings of the Korean Information Science Society Conference
• /
• 2010.06a
• /
• pp.17-18
• /
• 2010

• Proceedings of the Korean Information Science Society Conference
• /
• 2003.10b
• /
• pp.121-123
• /
• 2003

이동체 색인에 관한 기존 연구는 시간도메인에 따라 과거궤적에 대한 색인과 현재 및 미래위치색인 등으로 구분된다. 그러나 실 세계 응용에서는 과거 궤적뿐만 아니라 현재 및 미래위치를 모두 필요로 하는 경우가 많기 때문에 각 시간도메인 별로 두 개의 색인을 유지해야 하며 이 방법은 불필요한 비용을 필요로 한다. 따라서 과거, 현재, 미래에 대한 위치 데이터를 통합하여 불필요한 비용을 줄인 새로운 색인을 개발할 필요가 있다. 이 논문에서는 이동체의 과거궤적과 현재 및 미래위치데이터를 추상데이터 타입으로써 통합한 새로운 색인을 제안한다.