Performance Evaluation of Range Search Algorithm for k-dSLst Tree
Sumeet Gill1, Meenakshi2

1Sumeet Gill*, Department of Mathematics, M. D. University, Rohtak, Haryana, India.
2Meenakshi, Department of Mathematics, M. D. University, Rohtak, Haryana, India. 

Manuscript received on 01 August 2019. | Revised Manuscript received on 05 August 2019. | Manuscript published on 30 September 2019. | PP: 4432-4441 | Volume-8 Issue-3 September 2019 | Retrieval Number: C5544098319/2019©BEIESP | DOI: 10.35940/ijrte.C5544.098319
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: The indexing structures for spatial data are used to organize the data related to spatial objects with respect to their position. These indexing structures are indispensable in various applications like geographic information systems, robotics, computer graphics, CAD/CAM and many more. The range queries related to multiple dimensions are the crucial facet of many spatial applications. In this paper, we are introducing an algorithm kdSLst Objects In Range Search to search for spatial objects within a given range. We will be implementing this algorithm for k-dSLst tree, a spatial indexing tree based on k-d tree and linked list to store spatial data with duplicate keys, which we introduced in our earlier work. The experimental results show that the algorithm kdSLstObjectsInRangeSearch outperforms algorithm bruteForceRangeSearch based on brute force method of searching.
Keywords: Brute force, Indexing, k-d Tree, Range Search, Spatial

Scope of the Article:
High Performance Computing