research-article

EAR-Oracle: On Efficient Indexing for Distance Queries between Arbitrary Points on Terrain Surface

Authors:

Victor Junqiu Wei,

Raymond Chi-Wing Wong,

Bo TangAuthors Info & Claims

Proceedings of the ACM on Management of Data, Volume 1, Issue 1

Article No.: 14, Pages 1 - 26

https://doi.org/10.1145/3588694

Published: 30 May 2023 Publication History

Abstract

Due to the advancement of geo-positioning technology, the terrain data has become increasingly popular and has drawn a lot of research effort from both academia and industry. The distance computation on the terrain surface is a fundamental and important problem that is widely applied in geographical information systems and 3D modeling. As could be observed from the existing studies, online computation of the distance on the terrain surface is very expensive. All existing index-based methods are only efficient under the case where the distance query must be performed among a small set of predefined points-of-interest known apriori. But, in general cases, they could not scale up to sizable datasets due to their intolerable oracle building time and space consumption.

In this paper, we studied the arbitrary point-to-arbitrary point distance query on the terrain surface in which no assumption is imposed on the query points, and the distance query could be performed between any two arbitrary points. We propose an indexing structure, namely Efficient Arbitrary Point-to-Arbitrary Point Distance Oracle (EAR-Oracle), with theoretical guarantee on the accuracy, oracle building time, oracle size and query time. Our experiments demonstrate that our oracle enjoys excellent scalability and it scales up to enormous terrain surfaces but none of the existing index-based methods could be able to. Besides, it significantly outperforms all existing online computation methods by orders of magnitude in terms of the query time.

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Cited By

Yan YWong RJensen C(2025)An Efficiently Updatable Path Oracle for Terrain SurfacesIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2024.348443437:2(557-571)Online publication date: Feb-2025
https://doi.org/10.1109/TKDE.2024.3484434
Bača R(2024)Window Function Expression: Let the Self-Join EnterProceedings of the VLDB Endowment10.14778/3665844.366584817:9(2162-2174)Online publication date: 6-Aug-2024
https://dl.acm.org/doi/10.14778/3665844.3665848
Yan YWong R(2024)Proximity Queries on Point Clouds using Rapid Construction Path OracleProceedings of the ACM on Management of Data10.1145/36392612:1(1-26)Online publication date: 26-Mar-2024
https://dl.acm.org/doi/10.1145/3639261
Show More Cited By

Index Terms

EAR-Oracle: On Efficient Indexing for Distance Queries between Arbitrary Points on Terrain Surface
1. Information systems
  1. Data management systems
    1. Data structures
      1. Data access methods
        Proximity search

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cover image Proceedings of the ACM on Management of Data

Proceedings of the ACM on Management of Data Volume 1, Issue 1

PACMMOD

May 2023

2807 pages

EISSN:2836-6573

DOI:10.1145/3603164

Editor:
Divyakant Agrawal
UC Santa Barbara, United States

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Copyright © 2023 ACM.

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Publication History

Published: 30 May 2023

Published in PACMMOD Volume 1, Issue 1

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Cited By

Yan YWong RJensen C(2025)An Efficiently Updatable Path Oracle for Terrain SurfacesIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2024.348443437:2(557-571)Online publication date: Feb-2025
https://doi.org/10.1109/TKDE.2024.3484434
Bača R(2024)Window Function Expression: Let the Self-Join EnterProceedings of the VLDB Endowment10.14778/3665844.366584817:9(2162-2174)Online publication date: 6-Aug-2024
https://dl.acm.org/doi/10.14778/3665844.3665848
Yan YWong R(2024)Proximity Queries on Point Clouds using Rapid Construction Path OracleProceedings of the ACM on Management of Data10.1145/36392612:1(1-26)Online publication date: 26-Mar-2024
https://dl.acm.org/doi/10.1145/3639261
Yan YWong R(2024)Efficient Shortest Path Queries on 3D Weighted Terrain Surfaces for Moving Objects2024 25th IEEE International Conference on Mobile Data Management (MDM)10.1109/MDM61037.2024.00023(11-20)Online publication date: 24-Jun-2024
https://doi.org/10.1109/MDM61037.2024.00023

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