research-article

A NUMA-aware Trajectory Store for Travel-Time Estimation

Authors:

Christian S. Jensen,

Kristian TorpAuthors Info & Claims

SIGSPATIAL '19: Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems

Pages 209 - 218

https://doi.org/10.1145/3347146.3359371

Published: 05 November 2019 Publication History

Abstract

The increasingly massive volumes of vehicle trajectory data that are becoming available hold the potential to enable more accurate vehicle travel-time estimation than hitherto possible. To enable such uses, we present a multi-threaded, in-memory trajectory store that supports efficient and accurate travel-time estimation for road-network paths based on network-constrained trajectories. The trajectory store employs advanced indexing to support so-called strict-path queries that retrieve all trajectories that traverse a given path to provide accurate travel-time estimations. As a key novel feature, the store is designed and implemented to exploit modern non-uniform memory access (NUMA) systems. We provide a detailed experimental study of the performance of the trajectory store using a synthetic trajectory data set based on real traffic data. The study shows that query latency can be halved compared to our baseline system.

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Cited By

Gautam SRay SNickerson B(2021)Efficient Spatio-Textual Similarity Join Processing on NUMA Systems2021 22nd IEEE International Conference on Mobile Data Management (MDM)10.1109/MDM52706.2021.00022(79-88)Online publication date: Jun-2021
https://doi.org/10.1109/MDM52706.2021.00022
Gautam SRay SNickerson B(2020)NUMA-Aware Spatio-Textual Similarity JoinProceedings of the 28th International Conference on Advances in Geographic Information Systems10.1145/3397536.3422227(139-142)Online publication date: 3-Nov-2020
https://dl.acm.org/doi/10.1145/3397536.3422227

Index Terms

A NUMA-aware Trajectory Store for Travel-Time Estimation
1. Information systems
  1. Information systems applications
    1. Spatial-temporal systems

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cover image ACM Conferences

SIGSPATIAL '19: Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems

November 2019

648 pages

ISBN:9781450369091

DOI:10.1145/3347146

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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SIGSPATIAL: ACM Special Interest Group on Spatial Information

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New York, NY, United States

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Published: 05 November 2019

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SIGSPATIAL '19: 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems

November 5 - 8, 2019

IL, Chicago, USA

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SIGSPATIAL '19 Paper Acceptance Rate 34 of 161 submissions, 21%;

Overall Acceptance Rate 257 of 1,238 submissions, 21%

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Cited By

Gautam SRay SNickerson B(2021)Efficient Spatio-Textual Similarity Join Processing on NUMA Systems2021 22nd IEEE International Conference on Mobile Data Management (MDM)10.1109/MDM52706.2021.00022(79-88)Online publication date: Jun-2021
https://doi.org/10.1109/MDM52706.2021.00022
Gautam SRay SNickerson B(2020)NUMA-Aware Spatio-Textual Similarity JoinProceedings of the 28th International Conference on Advances in Geographic Information Systems10.1145/3397536.3422227(139-142)Online publication date: 3-Nov-2020
https://dl.acm.org/doi/10.1145/3397536.3422227

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