Optimizing Spatial Query Performance in Distributed GIS Architectures via Multi-Level Grid Indexing

International Journal of Computer Science and Technology | Vol. 4, No. 10, October 2023 | pp. 1–8

DOI: 10.46882/2023/IJCST/000225

Article Type: Original Research Paper

Title: Optimizing Spatial Query Performance in Distributed GIS Architectures via Multi-Level Grid Indexing

Names of Authors: Min-Ji Kim¹, David Miller²

Authors’ Affiliations: ¹Spatial Information Systems Lab, Pusan National University, Busan, South Korea; ²Geospatial Technologies Group, TechCorp Innovations, San Francisco, USA

Abstract: Distributed Geographic Information Systems (GIS) face major performance bottlenecks when executing complex spatial queries across multi-terabyte environmental datasets. Conventional indexing methods like standard R-trees encounter severe overlap issues when processing high-density urban coordinates, resulting in long query lookup delays. This paper proposes a multi-level grid indexing framework optimized for distributed spatial databases. The framework divides geographic coordinate spaces into hierarchical, non-overlapping grid cells, partitioning geospatial datasets balanced across cluster nodes. An adaptive spatial data placement algorithm balances workloads among servers based on historical query access frequencies. We validated this indexing architecture across a 16-node distributed cluster using a 500 GB global transport dataset. The experimental findings indicate a 44.1% reduction in total spatial query execution time compared to traditional distributed R-tree implementations. The cluster achieved a sustained query processing capacity of 12,400 queries per second, demonstrating its scalability for web-mapping infrastructures.

Keywords: Geographic Information Systems, Distributed Indexing, Spatial Queries, Grid Partitioning, Workload Balancing, Database Performance

Manuscript Timeline: Received: March 10, 2023; Revised: May 02, 2023; Accepted: June 15, 2023; Published: October 12, 2023

Citation: Kim, M. -J., & Miller, D. (2023). Optimizing Spatial Query Performance in Distributed GIS Architectures via Multi-Level Grid Indexing. International Journal of Computer Science and Technology, 4(10), 1–8. DOI: 10.46882/2023/IJCST/000225

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