hrcak mascot   Srce   HID

Izvorni znanstveni članak
https://doi.org/10.17559/TV-20170418094421

A MapReduce-Based Big Spatial Data Framework for Solving the Problem of Covering a Polygon with Orthogonal Rectangles

Süleyman Eken ; Department of Computer Engineering, Kocaeli University, Umuttepe Campus, 41380, İzmit, TURKEY
Ahmet Sayar ; Department of Computer Engineering, Kocaeli University, Umuttepe Campus, 41380, İzmit, TURKEY

Puni tekst: engleski, pdf (827 KB) str. 36-42 preuzimanja: 184* citiraj
APA 6th Edition
Eken, S. i Sayar, A. (2019). A MapReduce-Based Big Spatial Data Framework for Solving the Problem of Covering a Polygon with Orthogonal Rectangles. Tehnički vjesnik, 26 (1), 36-42. https://doi.org/10.17559/TV-20170418094421
MLA 8th Edition
Eken, Süleyman i Ahmet Sayar. "A MapReduce-Based Big Spatial Data Framework for Solving the Problem of Covering a Polygon with Orthogonal Rectangles." Tehnički vjesnik, vol. 26, br. 1, 2019, str. 36-42. https://doi.org/10.17559/TV-20170418094421. Citirano 22.11.2019.
Chicago 17th Edition
Eken, Süleyman i Ahmet Sayar. "A MapReduce-Based Big Spatial Data Framework for Solving the Problem of Covering a Polygon with Orthogonal Rectangles." Tehnički vjesnik 26, br. 1 (2019): 36-42. https://doi.org/10.17559/TV-20170418094421
Harvard
Eken, S., i Sayar, A. (2019). 'A MapReduce-Based Big Spatial Data Framework for Solving the Problem of Covering a Polygon with Orthogonal Rectangles', Tehnički vjesnik, 26(1), str. 36-42. https://doi.org/10.17559/TV-20170418094421
Vancouver
Eken S, Sayar A. A MapReduce-Based Big Spatial Data Framework for Solving the Problem of Covering a Polygon with Orthogonal Rectangles. Tehnički vjesnik [Internet]. 2019 [pristupljeno 22.11.2019.];26(1):36-42. https://doi.org/10.17559/TV-20170418094421
IEEE
S. Eken i A. Sayar, "A MapReduce-Based Big Spatial Data Framework for Solving the Problem of Covering a Polygon with Orthogonal Rectangles", Tehnički vjesnik, vol.26, br. 1, str. 36-42, 2019. [Online]. https://doi.org/10.17559/TV-20170418094421

Sažetak
The polygon covering problem is an important class of problems in the area of computational geometry. There are slightly different versions of this problem depending on the types of polygons to be addressed. In this paper, we focus on finding an answer to a question of whether an orthogonal rectangle, or spatial query window, is fully covered by a set of orthogonal rectangles which are in smaller sizes. This problem is encountered in many application domains including object recognition/extraction/trace, spatial analyses, topological analyses, and augmented reality applications. In many real-world applications, in the cases of using traditional central computation techniques, working with real world data results in a performance bottlenecks. The work presented in this paper proposes a high performance MapReduce-based big data framework to solve the polygon covering problem in the cases of using a spatial query window and data are represented as a set of orthogonal rectangles. Orthogonal rectangular polygons are represented in the form of minimum bounding boxes. The spatial query windows are also called as range queries. The proposed spatial big data framework is evaluated in terms of horizontal scalability. In addition, efficiency and speed-up performance metrics for the proposed two algorithms are measured.

Ključne riječi
big spatial data; GIS; MapReduce; polygon covering; spatial query

Hrčak ID: 217084

URI
https://hrcak.srce.hr/217084

Posjeta: 335 *