A foundation for efficient indoor distance-aware query processing

Indoor spaces accommodate large numbers of spatial objects, e.g., points of interest (POIs), and moving populations. A variety of services, e.g., location-based services and security control, are relevant to indoor spaces. Such services can be improved substantially if they are capable of utilizing...

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Main Authors: Jensen, Christian S., Lu, Hua, Cao, Xin
Other Authors: School of Computer Engineering
Format: Conference or Workshop Item
Language:English
Published: 2013
Subjects:
Online Access:https://hdl.handle.net/10356/99496
http://hdl.handle.net/10220/12982
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-994962020-05-28T07:17:45Z A foundation for efficient indoor distance-aware query processing Jensen, Christian S. Lu, Hua Cao, Xin School of Computer Engineering IEEE International Conference on Data Engineering (28th : 2012 : Washington, D. C., US) DRNTU::Engineering::Computer science and engineering Indoor spaces accommodate large numbers of spatial objects, e.g., points of interest (POIs), and moving populations. A variety of services, e.g., location-based services and security control, are relevant to indoor spaces. Such services can be improved substantially if they are capable of utilizing indoor distances. However, existing indoor space models do not account well for indoor distances. To address this shortcoming, we propose a data management infrastructure that captures indoor distance and facilitates distance-aware query processing. In particular, we propose a distance-aware indoor space model that integrates indoor distance seamlessly. To enable the use of the model as a foundation for query processing, we develop accompanying, efficient algorithms that compute indoor distances for different indoor entities like doors as well as locations. We also propose an indexing framework that accommodates indoor distances that are pre-computed using the proposed algorithms. On top of this foundation, we develop efficient algorithms for typical indoor, distance-aware queries. The results of an extensive experimental evaluation demonstrate the efficacy of the proposals. 2013-08-05T03:29:15Z 2019-12-06T20:08:05Z 2013-08-05T03:29:15Z 2019-12-06T20:08:05Z 2012 2012 Conference Paper https://hdl.handle.net/10356/99496 http://hdl.handle.net/10220/12982 10.1109/ICDE.2012.44 en
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic DRNTU::Engineering::Computer science and engineering
spellingShingle DRNTU::Engineering::Computer science and engineering
Jensen, Christian S.
Lu, Hua
Cao, Xin
A foundation for efficient indoor distance-aware query processing
description Indoor spaces accommodate large numbers of spatial objects, e.g., points of interest (POIs), and moving populations. A variety of services, e.g., location-based services and security control, are relevant to indoor spaces. Such services can be improved substantially if they are capable of utilizing indoor distances. However, existing indoor space models do not account well for indoor distances. To address this shortcoming, we propose a data management infrastructure that captures indoor distance and facilitates distance-aware query processing. In particular, we propose a distance-aware indoor space model that integrates indoor distance seamlessly. To enable the use of the model as a foundation for query processing, we develop accompanying, efficient algorithms that compute indoor distances for different indoor entities like doors as well as locations. We also propose an indexing framework that accommodates indoor distances that are pre-computed using the proposed algorithms. On top of this foundation, we develop efficient algorithms for typical indoor, distance-aware queries. The results of an extensive experimental evaluation demonstrate the efficacy of the proposals.
author2 School of Computer Engineering
author_facet School of Computer Engineering
Jensen, Christian S.
Lu, Hua
Cao, Xin
format Conference or Workshop Item
author Jensen, Christian S.
Lu, Hua
Cao, Xin
author_sort Jensen, Christian S.
title A foundation for efficient indoor distance-aware query processing
title_short A foundation for efficient indoor distance-aware query processing
title_full A foundation for efficient indoor distance-aware query processing
title_fullStr A foundation for efficient indoor distance-aware query processing
title_full_unstemmed A foundation for efficient indoor distance-aware query processing
title_sort foundation for efficient indoor distance-aware query processing
publishDate 2013
url https://hdl.handle.net/10356/99496
http://hdl.handle.net/10220/12982
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