Spatio-temporal joins on symbolic indoor tracking data

Hua Lu, Bin Yang, Christian S. Jensen

Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningpeer review

Abstract

To facilitate a variety of applications, positioning systems are deployed in indoor settings. For example, Bluetooth and RFID positioning are deployed in airports to support real-time monitoring of delays as well as off-line flow and space usage analyses. Such deployments generate large collections of tracking data. Like in other data management applications, joins are indispensable in this setting. However, joins on indoor tracking data call for novel techniques that take into account the limited capabilities of the positioning systems as well as the specifics of indoor spaces. This paper proposes and studies probabilistic, spatio-temporal joins on historical indoor tracking data. Two meaningful types of join are defined. They return object pairs that satisfy spatial join predicates either at a time point or during a time interval. The predicates considered include “same X,” where X is a semantic region such as a room or hallway. Based on an analysis on the uncertainty inherent to indoor tracking data, effective join probabilities are formalized and evaluated for object pairs. Efficient two-phase hash-based algorithms are proposed for the point and interval joins. In a filter-and-refine framework, an R-tree variant is proposed that facilitates the retrieval of join candidates, and pruning rules are supplied that eliminate candidate pairs that do not qualify. An empirical study on both synthetic and real data shows that the proposed techniques are efficient and scalable
OriginalsprogEngelsk
TitelProceedings of the 27th International Conference on Data Engineering, ICDE 2011, April 11-16, 2011, Hannover, Germany
RedaktørerSerge Abiteboul, Klemens Böhm, Christoph Koch, Kian-Lee Tan
Antal sider12
ForlagIEEE Computer Society Press
Publikationsdato2011
Sider816-827
ISBN (Trykt)978-1-4244-9194-0, 978-1-4244-8958-9
DOI
StatusUdgivet - 2011
Udgivet eksterntJa
Begivenhed27th IEEE International Conference on Data Engineering - Hannover, Tyskland
Varighed: 11 apr. 201116 apr. 2011
Konferencens nummer: 27

Konference

Konference27th IEEE International Conference on Data Engineering
Nummer27
Land/OmrådeTyskland
ByHannover
Periode11/04/201116/04/2011

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