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An efficient algorithm for maximizing range sum queries in a road network.

Tien-Khoi Phan1, HaRim Jung1, Ung-Mo Kim2

  • 1School of Information and Communication Engineering, Sungkyunkwan University, 2066 Seobu-ro, Jangan-gu, Suwon 440-746, Republic of Korea.

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This study introduces a new method for optimizing query rectangles in road networks, moving beyond standard Euclidean distance. The algorithm efficiently finds all optimal locations for maximizing point sums within network constraints.

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Area of Science:

  • Computational geometry
  • Database systems
  • Spatial analysis

Background:

  • Maximizing Range Sum (MaxRS) queries typically assume free movement in Euclidean space.
  • Real-world location-based applications often involve movement constrained by spatial road networks.
  • Existing MaxRS methods are not suitable for network-constrained environments.

Purpose of the Study:

  • To address the challenge of processing MaxRS queries within spatial road networks.
  • To develop an algorithm capable of handling large road network databases efficiently.
  • To identify all possible optimal locations for MaxRS queries, not just a single one.

Main Methods:

  • Proposed an external-memory algorithm specifically designed for large road network databases.
  • Adapted MaxRS query processing to account for network path constraints.
  • Developed a method to retrieve all optimal query rectangle locations.

Main Results:

  • The proposed external-memory algorithm is suitable for large-scale road network data.
  • The algorithm successfully retrieves all potential optimal locations for MaxRS queries.
  • Simulations demonstrated the performance of the developed algorithm.

Conclusions:

  • The new algorithm effectively processes MaxRS queries in road networks.
  • It provides a more comprehensive set of solutions compared to existing methods.
  • This approach enhances the utility of MaxRS queries in network-constrained applications.