Modeling and Processing for Next-Generation Big-Data Technologies Wi
This book covers the latest advances in Big Data technologies and provides the readers with a comprehensive review of the state-of-the-art in Big Data processing, analysis, analytics, and other related topics. It presents new models, algorithms, software
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Fatos Xhafa Leonard Barolli Admir Barolli Petraq Papajorgji Editors
Modeling and Processing for NextGeneration Big-Data Technologies With Applications and Case Studies
Modeling and Optimization in Science and Technologies Volume 4
Series editors Srikanta Patnaik, SOA University, Orissa, India e-mail: [email protected] Ishwar K. Sethi, Oakland University, Rochester, USA e-mail: [email protected] Xiaolong Li, Indiana State University, Terre Haute, USA e-mail: [email protected] Editorial Board Li Cheng, The Hong Kong Polytechnic University, Hong Kong Jeng-Haur Horng, National Formosa University, Yulin, Taiwan Pedro U. Lima, Institute for Systems and Robotics, Lisbon, Portugal Mun-Kew Leong, Institute of Systems Science, National University of Singapore Muhammad Nur, Diponegoro University, Semarang, Indonesia Luca Oneto, University of Genoa, Italy Kay Chen Tan, National University of Singapore, Singapore Sarma Yadavalli, University of Pretoria, South Africa Yeon-Mo Yang, Kumoh National Institute of Technology, Gumi, South Korea Liangchi Zhang, The University of New South Wales, Australia Baojiang Zhong, Soochow University, Suzhou, China Ahmed Zobaa, Brunel University, Uxbridge, Middlesex, UK
About this Series The book series Modeling and Optimization in Science and Technologies (MOST) publishes basic principles as well as novel theories and methods in the fast-evolving field of modeling and optimization. Topics of interest include, but are not limited to: methods for analysis, design and control of complex systems, networks and machines; methods for analysis, visualization and management of large data sets; use of supercomputers for modeling complex systems; digital signal processing; molecular modeling; and tools and software solutions for different scientific and technological purposes. Special emphasis is given to publications discussing novel theories and practical solutions that, by overcoming the limitations of traditional methods, may successfully address modern scientific challenges, thus promoting scientific and technological progress. The series publishes monographs, contributed volumes and conference proceedings, as well as advanced textbooks. The main targets of the series are graduate students, researchers and professionals working at the forefront of their fields. More information about this series at http://www.springer.com/series/10577
Fatos Xhafa · Leonard Barolli Admir Barolli · Petraq Papajorgji Editors
Modeling and Processing for Next-Generation Big-Data Technologies With Applications and Case Studies
ABC
Editors Fatos Xhafa Universitat Politècnica de Catalunya Barcelona Spain
Admir Barolli University of Salerno Salerno Italy
Leonard Barolli Fukuoka Institute of Technology (FIT) Fukuoka Japan
Petraq Papajorgji Canadian Institute of Technology Tirana Albania
ISSN 2196-7326 ISBN 978-3-319-09176-1 DOI 10.1007/978-3-319-09177-8
ISSN 2196-7334 (electronic) ISBN 978-3-319-09177-8 (eBook)
Library of Congress Control Number: 2014953522 Springer Cham Heidelberg New York D
