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Content Provider | IEEE Xplore Digital Library |
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Author | Hua Lu Xin Cao Jensen, C.S. |
Copyright Year | 2012 |
Abstract | 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. |
Starting Page | 438 |
Ending Page | 449 |
File Size | 478409 |
Page Count | 12 |
File Format | |
ISBN | 9781467300421 |
ISSN | 10844627 |
e-ISBN | 9780769547473 |
DOI | 10.1109/ICDE.2012.44 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2012-04-01 |
Publisher Place | USA |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Computational modeling Partitioning algorithms Legged locomotion Topology Buildings Solid modeling Query processing |
Content Type | Text |
Resource Type | Article |
Subject | Signal Processing Information Systems Software |
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