Description: Spatial Network Big Databases by Shashi Shekhar, KwangSoo Yang This book provides a collection of concepts, algorithms, and techniques that effectively harness the power of Spatial Network Big Data. 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. FORMAT Hardcover LANGUAGE English CONDITION Brand New Publisher Description 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. Table of Contents 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. Review "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) Review Quote "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) Feature Introduces an overview of Spatial Network Big Database Systems, including concepts related to data modeling, query processing, and storage methods Describes basic network algorithms that are used to design efficient spatial network query processing mechanisms Formulates the problem of query processing and storage methods and explores new algorithms that minimize the cost of data processing Details ISBN3319566563 Author KwangSoo Yang Year 2017 ISBN-10 3319566563 ISBN-13 9783319566566 Format Hardcover Pages 101 Language English Media Book Publication Date 2017-04-24 Imprint Springer International Publishing AG Subtitle Queries and Storage Methods Place of Publication Cham Country of Publication Switzerland Edition 1st Illustrations 62 Illustrations, black and white; XI, 101 p. 62 illus. Short Title Spatial Network Big Databases Publisher Springer International Publishing AG Edition Description 1st ed. 2017 Alternative 9783319859644 DEWEY 005.74 Audience Professional & Vocational We've got this At The Nile, if you're looking for it, we've got it. With fast shipping, low prices, friendly service and well over a million items - you're bound to find what you want, at a price you'll love! TheNile_Item_ID:127850412;
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ISBN-13: 9783319566566
Book Title: Spatial Network Big Databases
Subject Area: Regional History
Item Height: 235 mm
Item Width: 155 mm
Author: Kwangsoo Yang, Shashi Shekhar
Publication Name: Spatial Network Big Databases: Queries and Storage Methods
Format: Hardcover
Language: English
Publisher: Springer International Publishing Ag
Subject: Economics, Geography & Geosciences, Computer Science, Mathematics
Publication Year: 2017
Type: Study Guide
Item Weight: 362 g
Number of Pages: 101 Pages