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Indexing the positions of continuously moving objects

Authors:

Simonas Šaltenis,

Christian S. Jensen,

Scott T. Leutenegger,

Mario A. LopezAuthors Info & Claims

ACM SIGMOD Record, Volume 29, Issue 2

Pages 331 - 342

https://doi.org/10.1145/335191.335427

Published: 16 May 2000 Publication History

Abstract

The coming years will witness dramatic advances in wireless communications as well as positioning technologies. As a result, tracking the changing positions of objects capable of continuous movement is becoming increasingly feasible and necessary. The present paper proposes a novel, R*-tree based indexing technique that supports the efficient querying of the current and projected future positions of such moving objects. The technique is capable of indexing objects moving in one-, two-, and three-dimensional space. Update algorithms enable the index to accommodate a dynamic data set, where objects may appear and disappear, and where changes occur in the anticipated positions of existing objects. A comprehensive performance study is reported.

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Cited By

Wang YZeng YLi SZhang YZhou ZTong Y(2024)Efficient and Private Federated Trajectory MatchingIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2024.342441136:12(8079-8092)Online publication date: Dec-2024
https://doi.org/10.1109/TKDE.2024.3424411
Zhao XLam KKuo T(2024)Indexing spatiotemporal trajectory data streams on key-value storageComputing10.1007/s00607-024-01304-y106:8(2707-2735)Online publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1007/s00607-024-01304-y
Safaee SMirabi MRahmani ASafaei A(2023)A distributed B+Tree indexing method for processing range queries over streaming dataCluster Computing10.1007/s10586-023-04015-927:2(1251-1274)Online publication date: 7-May-2023
https://dl.acm.org/doi/10.1007/s10586-023-04015-9
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Index Terms

Indexing the positions of continuously moving objects
1. Information systems
  1. Information retrieval
    1. Document representation
  2. Information systems applications

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Information & Contributors

Information

Published In

cover image ACM SIGMOD Record

ACM SIGMOD Record Volume 29, Issue 2

June 2000

609 pages

ISSN:0163-5808

DOI:10.1145/335191

Editors:
Weidong Chen
Southern Methodist Univ., Dallas, TX
,
Jeffrey Naughton
Univ. of Wisconsin-Madison, Madison
,
Philip A. Bernstein
Microsoft

Issue’s Table of Contents

SIGMOD '00: Proceedings of the 2000 ACM SIGMOD international conference on Management of data
May 2000
604 pages
ISBN:1581132174
DOI:10.1145/342009
Chairmen:
Maggie Dunham
Southern Methodist Univ.
,
Jeffrey F. Naughton
Univ. of Wisconsin-Madison
,
Weidong Chen
Southern Methodist Univ.
,
Nick Koudas
AT &T Labs

Copyright © 2000 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 ACM 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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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 16 May 2000

Published in SIGMOD Volume 29, Issue 2

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Citations

Cited By

Wang YZeng YLi SZhang YZhou ZTong Y(2024)Efficient and Private Federated Trajectory MatchingIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2024.342441136:12(8079-8092)Online publication date: Dec-2024
https://doi.org/10.1109/TKDE.2024.3424411
Zhao XLam KKuo T(2024)Indexing spatiotemporal trajectory data streams on key-value storageComputing10.1007/s00607-024-01304-y106:8(2707-2735)Online publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1007/s00607-024-01304-y
Safaee SMirabi MRahmani ASafaei A(2023)A distributed B+Tree indexing method for processing range queries over streaming dataCluster Computing10.1007/s10586-023-04015-927:2(1251-1274)Online publication date: 7-May-2023
https://dl.acm.org/doi/10.1007/s10586-023-04015-9
Chen KLi CLu GLi JZhang T(2021)An Adaptive Parallel Method for Indexing Transportation Moving ObjectsComplexity10.1155/2021/66457782021(1-11)Online publication date: 22-Feb-2021
https://doi.org/10.1155/2021/6645778
Mondal AKakkar APadhariya NMohania M(2021)Efficient Indexing of Top-k Entities in Systems of Engagement with Extensions for Geo-tagged EntitiesData Science and Engineering10.1007/s41019-021-00173-1Online publication date: 11-Oct-2021
https://doi.org/10.1007/s41019-021-00173-1
Jiang WLi GAn JSun YChen HChen X(2020)A Survey of Moving Objects kNN Query in Road Network EnvironmentArtificial Intelligence in China10.1007/978-981-15-0187-6_75(629-636)Online publication date: 1-Feb-2020
https://doi.org/10.1007/978-981-15-0187-6_75
Hamdi WFaiz S(2020)Distributing Data in Real Time Spatial Data WarehouseAlgorithms and Architectures for Parallel Processing10.1007/978-3-030-60239-0_1(3-13)Online publication date: 2-Oct-2020
https://dl.acm.org/doi/10.1007/978-3-030-60239-0_1
Liu YPeng MShou G(2019)Mobile Edge Computing-Enhanced Proximity Detection in Time-Aware Road NetworksIEEE Access10.1109/ACCESS.2019.29373377(167958-167972)Online publication date: 2019
https://doi.org/10.1109/ACCESS.2019.2937337
Alamri STaniar DNguyen KAlamri A(2019)C-tree: efficient cell-based indexing of indoor mobile objectsJournal of Ambient Intelligence and Humanized Computing10.1007/s12652-019-01397-wOnline publication date: 17-Jul-2019
https://doi.org/10.1007/s12652-019-01397-w
Xu JGüting RZheng YWolfson O(2019)Moving Objects with Transportation Modes: A SurveyJournal of Computer Science and Technology10.1007/s11390-019-1938-434:4(709-726)Online publication date: 19-Jul-2019
https://doi.org/10.1007/s11390-019-1938-4
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