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A parallel GPU-based approach for reporting flock patterns

Data analysis and knowledge discovery in trajectory databases is an emerging field with a growing number of applications such as managing traffic, planning tourism infrastructures or better understanding wildlife. In this paper, we study the problem of finding flock patterns in trajectory databases. A flock refers to a large enough subset of entities that move close to each other for, at least, a given time interval. We present parallel algorithms, to be run on a Graphics Processing Unit, for reporting three different variants of the flock pattern: (1) all maximal flocks, (2) the largest flock and (3) the longest flock. We also provide their complexity analysis together with experimental results showing the efficiency and scalability of our approach

Work partially supported by the Spanish Ministerio de Ciencia e Innovación [TIN2010-20590-C02-02]

Taylor and Francis

Director: Ministerio de Ciencia e Innovación (Espanya)
Autor: Fort, Marta
Sellarès i Chiva, Joan Antoni
Valladares Cereceda, Ignacio
Data: 5 juny 2014
Resum: Data analysis and knowledge discovery in trajectory databases is an emerging field with a growing number of applications such as managing traffic, planning tourism infrastructures or better understanding wildlife. In this paper, we study the problem of finding flock patterns in trajectory databases. A flock refers to a large enough subset of entities that move close to each other for, at least, a given time interval. We present parallel algorithms, to be run on a Graphics Processing Unit, for reporting three different variants of the flock pattern: (1) all maximal flocks, (2) the largest flock and (3) the longest flock. We also provide their complexity analysis together with experimental results showing the efficiency and scalability of our approach
Work partially supported by the Spanish Ministerio de Ciencia e Innovación [TIN2010-20590-C02-02]
Format: application/pdf
Accés al document: http://hdl.handle.net/10256/13737
Llenguatge: eng
Editor: Taylor and Francis
Col·lecció: info:eu-repo/semantics/altIdentifier/doi/10.1080/13658816.2014.902949
info:eu-repo/semantics/altIdentifier/issn/1365-8816
info:eu-repo/semantics/altIdentifier/eissn/1365-8824
info:eu-repo/grantAgreement/MICINN//TIN2010-20590-C02-02/ES/AVANCES EN REALIDAD VIRTUAL PARA APLICACIONES PUNTERAS-UDG/
Drets: Tots els drets reservats
Matèria: Algorismes paral·lels
Parallel algorithms
Geometria computacional
Computational geometry
Títol: A parallel GPU-based approach for reporting flock patterns
Tipus: info:eu-repo/semantics/article
Repositori: DUGiDocs

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