Resource Management for Big Data Platforms Algorithms, Modelling, an
This book constitutes a flagship driver towards presenting and supporting advance research in the area of Big Data platforms and applications. Extracting valuable information from raw data is especially difficult considering the velocity of growing data f
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Florin Pop Joanna Kołodziej Beniamino Di Martino Editors
Resource Management for Big Data Platforms Algorithms, Modelling, and HighPerformance Computing Techniques
Computer Communications and Networks Series editor A.J. Sammes Centre for Forensic Computing Cranfield University, Shrivenham Campus Swindon, UK
The Computer Communications and Networks series is a range of textbooks, monographs and handbooks. It sets out to provide students, researchers, and non-specialists alike with a sure grounding in current knowledge, together with comprehensible access to the latest developments in computer communications and networking. Emphasis is placed on clear and explanatory styles that support a tutorial approach, so that even the most complex of topics is presented in a lucid and intelligible manner.
More information about this series at http://www.springer.com/series/4198
Florin Pop Joanna Kołodziej Beniamino Di Martino •
Editors
Resource Management for Big Data Platforms Algorithms, Modelling, and High-Performance Computing Techniques
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Editors Florin Pop University Politehnica of Bucharest Bucharest Romania
Beniamino Di Martino Second University of Naples Naples, Caserta Italy
Joanna Kołodziej Cracow University of Technology Cracow Poland
ISSN 1617-7975 ISSN 2197-8433 (electronic) Computer Communications and Networks ISBN 978-3-319-44880-0 ISBN 978-3-319-44881-7 (eBook) DOI 10.1007/978-3-319-44881-7 Library of Congress Control Number: 2016948811 © Springer International Publishing AG 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 International Publishing AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland
To our Families and Friends with Love and Gratitude
Preface
Many applications generate Big Data, like social networking and social influence programs, Cloud applications, public web sites, scientific experiments a
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