Smart Data: State-of-the-Art Perspectives in Computing and Applications

by Kuan-Ching Li (Editor), Beniamino Di Martino (Editor), Laurence T. Yang (Editor), Qingchen Zhang (Editor)

Overview

Smart Data: State-of-the-Art Perspectives in Computing and Applications explores smart data computing techniques to provide intelligent decision making and prediction services support for business, science, and engineering. It also examines the latest research trends in fields related to smart data computing and applications, including new computing theories, data mining and machine learning techniques. The book features contributions from leading experts and covers cutting-edge topics such as smart data and cloud computing, AI for networking, smart data deep learning, Big Data capture and representation, AI for Big Data applications, and more.

Features

• Presents state-of-the-art research in big data and smart computing
• Provides a broad coverage of topics in data science and machine learning
• Combines computing methods with domain knowledge and a focus on applications in science, engineering, and business
• Covers data security and privacy, including AI techniques
• Includes contributions from leading researchers

Product Details

ISBN-13:	9781138545588
Publisher:	Taylor & Francis
Publication date:	03/13/2019
Series:	Chapman & Hall/CRC Big Data Series
Pages:	428
Product dimensions:	7.00(w) x 10.00(h) x (d)

About the Author

Kuan-Ching Li, Beniamino Di Martino, Laurence T. Yang, Qingchen Zhang

Table of Contents

Foreword, ix

Acknowledgement, xi

Editors, xiii

List of Contributors, xv

CHAPTER 1 ■ Extreme Heterogeneity in Deep Learning Architectures 1

JEFF ANDERSON, ARMIN MEHRABIAN, JIAXIN PENG, AND TAREK EL-GHAZAWI

CHAPTER 2 ■ GPU PaaS Computation Model in Aneka Cloud

Computing Environments 19

SHASHIKANT ILAGER, RAJEEV WANKAR, RAGHAVENDRA KUNE, AND RAJKUMAR BUYYA

CHAPTER 3 ■ Toward Complex Search for Encrypted Mobile Cloud

Data via Index Blind Storage 41

YUPENG HU, LINJUN WU, WENJIA LI, KEQIN LI, YONGHE LIU, AND ZHENG QIN

CHAPTER 4 ■ Encrypted Big Data Deduplication in Cloud Storage 63

ZHENG YAN, XUEQIN LIANG, WENXIU DING, XIXUN YU, MINGJUN WANG, AND

ROBERT H. DENG

CHAPTER 5 ■ The Role of NonSQL Databases in Big Data 93

ANTONIO SARASA CABEZUELO

CHAPTER 6 ■ Prescriptive and Predictive Analytics Techniques for

Enabling Cybersecurity 113

NITIN SUKHIJA, SONNY SEVIN, ELIZABETH BAUTISTA, AND DAVID DAMPIER

CHAPTER 7 ■ Multivariate Projection Techniques to Reduce

Dimensionality in Large Datasets 133

I. BARRANCO CHAMORRO, S. MUÑOZ-ARMAYONES, A. ROMERO-LOSADA,

AND F. ROMERO-CAMPERO

CHAPTER 8 ■ Geo-Distributed Big Data Analytics Systems: An

Online Learning Approach for Dynamic Deployment 161

YIXIN BAO AND CHUAN WU

CHAPTER 9 ■ The Role of Smart Data in Inference of Human Behavior

and Interaction 191

RUTE C. SOFIA, LILIANA CARVALHO, AND FRANCISCO M. PEREIRA

CHAPTER 10 ■ Compression of Wearable Body Sensor Network Data 215

ROBINSON RAJU, MELODY MOH, AND TENG-SHENG MOH

CHAPTER 11 ■ Population-Specific and Personalized (PSP) Models of

Human Behavior for Leveraging Smart and

Connected Data 243

THEODORA CHASPARI, ADELA C. TIMMONS, AND GAYLA MARGOLIN

CHAPTER 12 ■ Detecting Singular Data for Better Analysis of

Emotional Tweets 259

KIICHI TAGO, KENICHI ITO, AND QUN JIN

CHAPTER 13 ■ Smart Data Infrastructure for Respiratory Health

Protection of Citizens against PM2.5 in Urban Areas 273

DANIEL DUNEA, STEFANIA IORDACHE, ALIN POHOATA, AND EMIL LUNGU

CHAPTER 14 ■ Fog-Assisted Cloud Platforms for Big Data Analytics in

Cyber Physical Systems: A Smart Grid Case Study 289

MD. MUZAKKIR HUSSAIN, MOHAMMAD SAAD ALAM, AND M.M. SUFYAN BEG

CHAPTER 15 ■ When Big Data and Data Science Prefigured Ambient

Intelligence 319

CHRISTOPHE THOVEX

CHAPTER 16 ■ Ethical Issues and Considerations of Big Data 343

EDWARD T. CHEN

CHAPTER 17 ■ Data Protection by Design in Smart Data Environments 359

PAOLO BALBONI

INDEX, 391

Editorial Reviews

"The book is a great resource for all those interested in learning about the interplay between "smart data" and a number of research themes: algorithms, applications, ethical issues, security and data privacy, among many other topics. The book will be very useful for researchers, practitioners, and graduate students; a welcome addition to the Smart Data literature. The book is a milestone in this fast-moving field."
— Professor Albert Y. Zomaya, Sydney University, Australia

"This book provides a precious set of high-level research contributions for learning how to extract Smart Data from Big Data. Novel intelligent techniques, models, algorithms and applications are presented and discussed. Young researchers and professionals will benefit from the book contents to learn new topics and investigate new research issues. From infrastructure and algorithms to applications and ethics, Smart Data are illustrated and put in practice."

— Professor Domenico Talia, Università della Calabria, Italy

From the Publisher