Kd-tree and quad-tree decompositions for declustering of 2D range queries over uncertain space

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Atıf İçin Kopyala

SAYAR A., EKEN S., OZTURK O.

FRONTIERS OF INFORMATION TECHNOLOGY & ELECTRONIC ENGINEERING, cilt.16, sa.2, ss.98-108, 2015 (SCI-Expanded)

• Yayın Türü: Makale / Tam Makale
• Cilt numarası: 16 Sayı: 2
• Basım Tarihi: 2015
• Doi Numarası: 10.1631/fitee.1400165
• Dergi Adı: FRONTIERS OF INFORMATION TECHNOLOGY & ELECTRONIC ENGINEERING
• Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
• Sayfa Sayıları: ss.98-108
• Kocaeli Üniversitesi Adresli: Evet

Özet

We present a study to show the possibility of using two well-known space partitioning and indexing techniques, kd trees and quad trees, in declustering applications to increase input/output (I/O) parallelization and reduce spatial data processing times. This parallelization enables time-consuming computational geometry algorithms to be applied efficiently to big spatial data rendering and querying. The key challenge is how to balance the spatial processing load across a large number of worker nodes, given significant performance heterogeneity in nodes and processing skews in the workload.