research-article

A Query Optimizer for Range Queries over Multi-Attribute Trajectories

Authors:

Zhifeng BaoAuthors Info & Claims

ACM Transactions on Intelligent Systems and Technology, Volume 14, Issue 1

Article No.: 12, Pages 1 - 28

https://doi.org/10.1145/3555811

Published: 27 January 2023 Publication History

Abstract

A multi-attribute trajectory consists of a spatio-temporal trajectory and a set of descriptive attributes. Such data enrich the representation of traditional spatio-temporal trajectories to have comprehensive knowledge of moving objects. Range query is a fundamental operator over multi-attribute trajectories. Such a query contains two predicates, spatio-temporal and attribute, and returns the objects whose locations are within a distance threshold to the query trajectory and attributes contain expected values. There are different execution plans for answering the query. To enhance the capability of a trajectory database, an optimizer is essentially required to (i) accurately estimate the cost for alternative query strategies in terms of disk accesses, (ii) build a decision-making module that automatically sorts the data in an appropriate way and selects the optimal query plan, and (iii) update the analytical models when new trajectories are arrived. The cost model supports both uniform and non-uniform spatio-temporal data distribution and incorporates attribute distribution. The optimizer is fully developed inside a database system kernel and comprehensively evaluated in terms of accuracy and effectiveness by using large real and synthetic datasets.

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Cited By

Xu MChen XShe YJin YZhao GWang J(2024)Strengthening Cooperative Consensus in Multi-Robot ConfrontationACM Transactions on Intelligent Systems and Technology10.1145/363937115:2(1-27)Online publication date: 22-Feb-2024
https://dl.acm.org/doi/10.1145/3639371
Xu MShe YJin YWang J(2023)Dynamic Weights and Prior Reward in Policy Fusion for Compound Agent LearningACM Transactions on Intelligent Systems and Technology10.1145/362340514:6(1-28)Online publication date: 14-Nov-2023
https://dl.acm.org/doi/10.1145/3623405
Ye SLu J(undefined)Robust Recommender Systems with Rating Flip NoiseACM Transactions on Intelligent Systems and Technology10.1145/3641285
https://dl.acm.org/doi/10.1145/3641285

Index Terms

A Query Optimizer for Range Queries over Multi-Attribute Trajectories
1. Information systems
  1. Data management systems
  2. Information systems applications
    1. Spatial-temporal systems

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Published In

cover image ACM Transactions on Intelligent Systems and Technology

ACM Transactions on Intelligent Systems and Technology Volume 14, Issue 1

February 2023

487 pages

ISSN:2157-6904

EISSN:2157-6912

DOI:10.1145/3570136

Editor:
Huan Liu
Arizona State University, USA

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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

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Publication History

Published: 27 January 2023

Online AM: 10 September 2022

Accepted: 19 July 2022

Revised: 15 June 2022

Received: 05 December 2021

Published in TIST Volume 14, Issue 1

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NSFC
Natural Science Foundation of Jiangsu Province of China

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Cited By

Xu MChen XShe YJin YZhao GWang J(2024)Strengthening Cooperative Consensus in Multi-Robot ConfrontationACM Transactions on Intelligent Systems and Technology10.1145/363937115:2(1-27)Online publication date: 22-Feb-2024
https://dl.acm.org/doi/10.1145/3639371
Xu MShe YJin YWang J(2023)Dynamic Weights and Prior Reward in Policy Fusion for Compound Agent LearningACM Transactions on Intelligent Systems and Technology10.1145/362340514:6(1-28)Online publication date: 14-Nov-2023
https://dl.acm.org/doi/10.1145/3623405
Ye SLu J(undefined)Robust Recommender Systems with Rating Flip NoiseACM Transactions on Intelligent Systems and Technology10.1145/3641285
https://dl.acm.org/doi/10.1145/3641285

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