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Geographic Information Systems (GIS) operate across three levels of application, each representing an increasing degree of complexity: data management, analysis, and prediction. These levels reflect the expanding functionality and versatility of GIS technology in handling spatial data for diverse purposes.Data ManagementAt its foundational level, GIS serves as a tool for data management, enabling the input, storage, retrieval, and organization of spatial data. This level is often employed in...
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A Global User-Driven Model for Tile Prefetching in Web Geographical Information Systems.

Shaoming Pan1, Yanwen Chong1, Hang Zhang2

  • 1State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, Hubei, China.

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|January 14, 2017
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Summary
This summary is machine-generated.

This study introduces a new global user-driven model for web geographical information system tile prefetching and cache replacement. The model significantly improves prefetching hit rates by considering all users' access behaviors and tile relationships.

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Area of Science:

  • Computer Science
  • Geographic Information Systems

Background:

  • Web geographical information systems (GIS) are service-intensive applications.
  • Tile prefetching and cache replacement enhance performance by reducing disk latency.
  • Existing strategies often focus on individual user behavior or tile popularity, limiting potential improvements.

Purpose of the Study:

  • To propose a novel global user-driven model for tile prefetching and cache replacement in web GIS.
  • To enhance cache hit ratios and system access performance by considering collective user behavior and tile correlations.

Main Methods:

  • Developed an expression method to quantify tile correlation based on aggregated user access patterns.
  • Implemented a conditional prefetching probability calculation to identify tiles for prefetching and replacement.
  • Conducted experiments comparing the proposed model against existing prefetching strategies.

Main Results:

  • The proposed global user-driven model demonstrated superior performance.
  • Achieved prefetching hit rates approximately 10.6% to 110.5% higher than compared methods.
  • Indicated the benefit of a holistic approach considering all users and tile interdependencies.

Conclusions:

  • The new model effectively improves web GIS performance through intelligent tile management.
  • Comprehensive analysis of user behavior and tile relationships is crucial for optimal prefetching.
  • This approach offers a significant advancement over single-user or popularity-based prefetching strategies.