1st Edition
Smart Data State-of-the-Art Perspectives in Computing and Applications
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
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
Biography
Kuan-Ching Li, Beniamino Di Martino, Laurence T. Yang, Qingchen Zhang
"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
