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Spatio-Temporal Data Streams [electronic resource] / by Zdravko Galić.

By: Galić, Zdravko [author.].
Contributor(s): SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: SpringerBriefs in Computer Science: Publisher: New York, NY : Springer New York : Imprint: Springer, 2016Description: XIV, 107 p. 28 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9781493965755.Subject(s): Computer science | Computer communication systems | Database management | Geographical information systems | Graph theory | Computer Science | Database Management | Geographical Information Systems/Cartography | Computer Communication Networks | Graph TheoryAdditional physical formats: Printed edition:: No titleDDC classification: 005.74 Online resources: Click here to access online
Contents:
Introduction -- Spatio-Temporal Continuous Queries -- Spatio-Temporal Data Streams and Big Data Paradigm -- Spatio-Temporal Data Stream Clustering.
In: Springer eBooksSummary: This SpringerBrief presents the fundamental concepts of a specialized class of data stream, spatio-temporal data streams, and demonstrates their distributed processing using Big Data frameworks and platforms. It explores a consistent framework which facilitates a thorough understanding of all different facets of the technology, from basic definitions to state-of-the-art techniques. Key topics include spatio-temporal continuous queries, distributed stream processing, SQL-like language embedding, and trajectory stream clustering. Over the course of the book, the reader will become familiar with spatio-temporal data streams management and data flow processing, which enables the analysis of huge volumes of location-aware continuous data streams. Applications range from mobile object tracking and real-time intelligent transportation systems to traffic monitoring and complex event processing. Spatio-Temporal Data Streams is a valuable resource for researchers studying spatio-temporal data streams and Big Data analytics, as well as data engineers and data scientists solving data management and analytics problems associated with this class of data.
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Introduction -- Spatio-Temporal Continuous Queries -- Spatio-Temporal Data Streams and Big Data Paradigm -- Spatio-Temporal Data Stream Clustering.

This SpringerBrief presents the fundamental concepts of a specialized class of data stream, spatio-temporal data streams, and demonstrates their distributed processing using Big Data frameworks and platforms. It explores a consistent framework which facilitates a thorough understanding of all different facets of the technology, from basic definitions to state-of-the-art techniques. Key topics include spatio-temporal continuous queries, distributed stream processing, SQL-like language embedding, and trajectory stream clustering. Over the course of the book, the reader will become familiar with spatio-temporal data streams management and data flow processing, which enables the analysis of huge volumes of location-aware continuous data streams. Applications range from mobile object tracking and real-time intelligent transportation systems to traffic monitoring and complex event processing. Spatio-Temporal Data Streams is a valuable resource for researchers studying spatio-temporal data streams and Big Data analytics, as well as data engineers and data scientists solving data management and analytics problems associated with this class of data.

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