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


SAYAR A. , EKEN S. , OZTURK O.

FRONTIERS OF INFORMATION TECHNOLOGY & ELECTRONIC ENGINEERING, cilt.16, ss.98-108, 2015 (SCI İndekslerine Giren Dergi) identifier identifier

  • Cilt numarası: 16 Konu: 2
  • Basım Tarihi: 2015
  • Doi Numarası: 10.1631/fitee.1400165
  • Dergi Adı: FRONTIERS OF INFORMATION TECHNOLOGY & ELECTRONIC ENGINEERING
  • Sayfa Sayıları: ss.98-108

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.