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DOS: a spatial system offering extremely high-throughput road distance computations

Authors:

Jagan Sankaranarayanan,

Hanan SametAuthors Info & Claims

SIGSPATIAL '18: Proceedings of the 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems

Pages 199 - 208

https://doi.org/10.1145/3274895.3274898

Published: 06 November 2018 Publication History

Abstract

Large analytic applications on road networks including simulations, logistics, location-based advertisement, and transportation planning require shortest distance/time methods that provide high throughput (i.e., distance/time computations per second). Our previous work discussed how to process graph distance computations in a PostgreSQL database on a large road network, e.g., 60K distance computations per second per machine, how to "scale out" by using a Spark cluster to achieve 73.8K distance computations per second per machine, and how to obtain a extremely high-throughput solution in memory for city-sized road networks, e.g., 6.7M distance computations per second. However, there is no solution that could achieve more than 1M throughput for large road networks. In an industrial setting, most state-of-the-art solutions yield 5K - 10K shortest distance computations per second per machine even with multi-threads. In this paper, we propose a new distance oracle system (DOS) for large road networks. It can solve most spatial analytic queries, and its throughput achieves 5M distance computations per second even on the whole USA road network. For example, a 10K × 10K origin-distance (OD) matrix can be computed in 20 seconds.

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Cited By

Ghosh DSankaranarayanan JKhatter KSamet H(2023)In-Path Oracles for Road NetworksISPRS International Journal of Geo-Information10.3390/ijgi1207027712:7(277)Online publication date: 13-Jul-2023
https://doi.org/10.3390/ijgi12070277
Ghosh DSankaranarayanan JKhatter KSamet H(2023)Opportunistic package delivery as a service on road networksGeoInformatica10.1007/s10707-023-00497-228:1(53-88)Online publication date: 3-Jun-2023
https://doi.org/10.1007/s10707-023-00497-2
Ayhan SCostas PSamet H(2019)A Data-driven Framework for Long-Range Aircraft Conflict Detection and ResolutionACM Transactions on Spatial Algorithms and Systems10.1145/33288325:4(1-23)Online publication date: 12-Sep-2019
https://dl.acm.org/doi/10.1145/3328832

Index Terms

DOS: a spatial system offering extremely high-throughput road distance computations
1. Information systems
  1. Data management systems
    1. Database management system engines
      1. Database query processing
  2. Information systems applications
    1. Spatial-temporal systems

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Published In

cover image ACM Conferences

SIGSPATIAL '18: Proceedings of the 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems

November 2018

655 pages

ISBN:9781450358897

DOI:10.1145/3274895

General Chairs:
Farnoush Banaei-Kashani
University of Colorado, Denver
,
Erik Hoel
Esri
,
Program Chairs:
Ralf Hartmut Güting
FernUniversität in Hagen, Germany
,
Roberto Tamassia
Brown University
,
Li Xiong
Emory University

Copyright © 2018 ACM.

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SIGSPATIAL: ACM Special Interest Group on Spatial Information

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Association for Computing Machinery

New York, NY, United States

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Published: 06 November 2018

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SIGSPATIAL

SIGSPATIAL '18: 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems

November 6 - 9, 2018

Washington, Seattle

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SIGSPATIAL '18 Paper Acceptance Rate 30 of 150 submissions, 20%;

Overall Acceptance Rate 220 of 1,116 submissions, 20%

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Cited By

Ghosh DSankaranarayanan JKhatter KSamet H(2023)In-Path Oracles for Road NetworksISPRS International Journal of Geo-Information10.3390/ijgi1207027712:7(277)Online publication date: 13-Jul-2023
https://doi.org/10.3390/ijgi12070277
Ghosh DSankaranarayanan JKhatter KSamet H(2023)Opportunistic package delivery as a service on road networksGeoInformatica10.1007/s10707-023-00497-228:1(53-88)Online publication date: 3-Jun-2023
https://doi.org/10.1007/s10707-023-00497-2
Ayhan SCostas PSamet H(2019)A Data-driven Framework for Long-Range Aircraft Conflict Detection and ResolutionACM Transactions on Spatial Algorithms and Systems10.1145/33288325:4(1-23)Online publication date: 12-Sep-2019
https://dl.acm.org/doi/10.1145/3328832

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