Spatial Network Big Databases
Queries and Storage Methods
(Sprache: Englisch)
This book provides a collection of concepts, algorithms, and techniques that effectively harness the power of Spatial Network Big Data. Reading this book is a first step towards understanding the immense challenges and novel applications of SNBD database...
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This book provides a collection of concepts, algorithms, and techniques that effectively harness the power of Spatial Network Big Data. Reading this book is a first step towards understanding the immense challenges and novel applications of SNBD database systems. This book explores these challenges via investigating scalable graph-based query processing strategies and I/O efficient storage and access methods. This book will be of benefit to academics, researchers, engineers with a particular interest in network database models, network query processing, and physical storage models.Inhaltsverzeichnis zu „Spatial Network Big Databases “
1. Spatial Network Big Databases: An Introduction.- 2. Basic Graph Algorithms.- 3. Capacity Constrained Network Voronoi Diagrams.- 4. Distance-Constrained k Spatial Sub-Networks.- 5. Evacuation Route Planning.- 6. Storage Schemes for Spatio-temporal Network Datasets.- 7. Summary.
Bibliographische Angaben
- Autoren: KwangSoo Yang , Shashi Shekhar
- 2017, 1st ed. 2017, XI, 101 Seiten, Maße: 15,9 x 24,4 cm, Gebunden, Englisch
- Verlag: Springer, Berlin
- ISBN-10: 3319566563
- ISBN-13: 9783319566566
- Erscheinungsdatum: 24.04.2017
Sprache:
Englisch
Pressezitat
"Spatial network big data (SNBD) can be widely found in every corner of modern society. Examples include temporally detailed road maps that provide car speeds every minute for every road segment and GPS trace data from our cell phones. ... The topic of this book is attractive and beneficial to readers and researchers who are interested in spatial networks, graph data, big data, and databases. It includes a clear structure when introducing the basic information, existing methods, and practical applications." (Feng Yu, Computing Reviews, January, 4, 2018)
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