Adaptive cell-based index for moving objects

Choi, Wonik; Moon, Bongki; Lee, Suk-Ho

doi:10.1016/s0169-023x(03)00120-4

Cited by 17 publications

(14 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The former had a pointer to the next coming node and distances of all nodes; thus, it had the disadvantage of taking a considerable amount of time to calculate them in advance [24−25]. The latter required all adjacent nodes around a node to be checked, resulting in a large I/O process [19]. Reference [26] aimed to solve the weaknesses presented in the previous studies.…”

Section: Road Network Based Spatial Query Processingmentioning

confidence: 99%

Bitmap lattice index in road networks

Song

Lee

Park

2014

J. Cent. South Univ.

View full text Add to dashboard Cite

A novel technique called the bitmap lattice index (BLI) is proposed, which combines the advantages of a wireless broadcasting environment with a road network. Existing road networks are based on the on-demand method: a server's workload increases as the query request increases when a server sends a client information. To solve this problem, we propose the BLI. The BLI denotes an object and a node as 0 and 1 in the Hilbert curve (HC) map. The BLI can identify the position of a node and an object through bit information; it can also reduce the broadcasting frequency of a server by reducing the size of the index, thereby decreasing the access latency and query processing times. Moreover, the BLI is highly effective for data filtering, as it can identify the positions of both an object and a node. In a road network, if filtering is done via the Euclidean distance, it may result in an error. To prevent this, we add another validation procedure. The experiment is conducted by applying the BLI to kNN query, and the technique is assessed by a performance evaluation experiment.

show abstract

Section: Road Network Based Spatial Query Processingmentioning

confidence: 99%

Bitmap lattice index in road networks

Song

Lee

Park

2014

J. Cent. South Univ.

View full text Add to dashboard Cite

show abstract

“…movements of objects) and can be used to explore the movement observations of an object over time and space. Volumetric visualization techniques can be used in the 3106 E. Beşdok and H. M. Palancioglu analysis of movement behaviours of objects (Choi et al 2003(Choi et al , 2004. The perception of changes in the observed movement parameters is facilitated with a datavisualization approach.…”

Section: Volumetric Visualizationmentioning

confidence: 99%

“…An approach of indexing the movements of objects is introduced in Choi et al (2004). The approach adopts a cell-based index structure for the current and historical information on moving objects.…”

Section: Introductionmentioning

confidence: 99%

“…The approach adopts a cell-based index structure for the current and historical information on moving objects. It proposes a new structure called ATM (Adaptive cell-based Index for Moving objects) to deal with the problems of R-tree-based access methods (Choi et al 2004). The ATM consumes only 30% of the space required by the R-tree based methods and demonstrates a higher query performance.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Modelling uncertainties related to movements of objects through signatures

Palancioglu

2005

International Journal of Remote Sensing

View full text Add to dashboard Cite

Moving objects have changing and repeating patterns due to their movements in space over time. A set of observations on a moving object can be used to derive the movement patterns by summarizing frequently visited locations and frequently used paths over time by the object. These space-and time-dependent movement patterns of an object are referred to as spatio-temporal movement signatures in this paper. There is a need to understand and identify the spatiotemporal movement signatures. Analysis of the spatio-temporal movement signatures can help improve the modelling, querying, and reasoning capabilities of the movements of objects. This paper demonstrates the extraction of movement signatures from sets of movement observations using Visualization and Resilient Neural Network methodologies. Identification of movement signatures and definition of their attributes provide summary-level information for modelling and reasoning about moving objects.

show abstract

“…These services need to know the current positions of objects quickly. The index structure should be adaptive and dynamic to keep track of the positions of objects and to provide quick answers to the expected queries [1].…”

Section: Introductionmentioning

confidence: 99%