Spatio-Temporal Data Streams
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 facil
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Zdravko Galić
Spatio-Temporal Data Streams
123
SpringerBriefs in Computer Science Series editors Stan Zdonik Shashi Shekhar Jonathan Katz Xindong Wu Lakhmi C. Jain David Padua Xuemin (Sherman) Shen Borko Furht V.S. Subrahmanian Martial Hebert Katsushi Ikeuchi Bruno Siciliano Sushil Jajodia Newton Lee
More information about this series at http://www.springer.com/series/10028
Zdravko Galić
Spatio-Temporal Data Streams
123
Zdravko Galić Faculty of Electrical Engineering and Computing University of Zagreb Zagreb Croatia
ISSN 2191-5768 ISSN 2191-5776 (electronic) SpringerBriefs in Computer Science ISBN 978-1-4939-6573-1 ISBN 978-1-4939-6575-5 (eBook) DOI 10.1007/978-1-4939-6575-5 Library of Congress Control Number: 2016947747 © The Author(s) 2016 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. Printed on acid-free paper This Springer imprint is published by Springer Nature The registered company is Springer Science+Business Media LLC New York
In loving memory of my mother Pavica (Lončar) Galić for all her love, care and support.
Preface
Recent advances in the information and communication technologies, especially the rapid development of wireless communication, sensor networks, mobile computing technologies, global navigational satellite systems (GPS, GLONASS, COMPASS, Galileo), RFID, wireless sensor networks and spatially enabled devices are leading to an exponential growth in the amount of available data produced continuously at hight speed. Due to the advancements in recent years, a new class of applications has come to the forefront: sensor networks, moving objects tracking, homeland security, fleet management, real-time intelligent transportation systems, etc. Applications in these novel domains process huge volumes of continuous streaming data, i.e. data that is produced incrementally over time, rather than being available fully before processing. According to the type of processing, data stream processing could be broadly classified into two categories: data
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