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

DescriptionSmart 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.Key FeaturesPresents state-of-the-art research in big data and smart computingProvides a broad coverage of topics in data science and machine learningCombines computing methods with domain knowledge and a focus on applications in science, engineering, and businessCovers data security and privacy, including AI techniquesIncludes contributions from leading researchersTable of ContentsForeword, ixAcknowledgement, xiEditors, xiiiList of Contributors, xvCHAPTER 1: Extreme Heterogeneity in Deep Learning Architectures 1 – JEFF ANDERSON, ARMIN MEHRABIAN, JIAXIN PENG, AND TAREK EL-GHAZAWICHAPTER 2: GPU PaaS Computation Model in Aneka Cloud Computing Environments 19 – SHASHIKANT ILAGER, RAJEEV WANKAR, RAGHAVENDRA KUNE, AND RAJKUMAR BUYYACHAPTER 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 QINCHAPTER 4: Encrypted Big Data Deduplication in Cloud Storage 63 – ZHENG YAN, XUEQIN LIANG, WENXIU DING, XIXUN YU, MINGJUN WANG, AND ROBERT H. DENGCHAPTER 5: The Role of NonSQL Databases in Big Data 93 – ANTONIO SARASA CABEZUELOCHAPTER 6: Prescriptive and Predictive Analytics Techniques for Enabling Cybersecurity 113 – NITIN SUKHIJA, SONNY SEVIN, ELIZABETH BAUTISTA, AND DAVID DAMPIERCHAPTER 7: Multivariate Projection Techniques to Reduce Dimensionality in Large Datasets 133 – I. BARRANCO CHAMORRO, S. MUÑOZ-ARMAYONES, A. ROMERO-LOSADA, AND F. ROMERO-CAMPEROCHAPTER 8: Geo-Distributed Big Data Analytics Systems: An Online Learning Approach for Dynamic Deployment 161 – YIXIN BAO AND CHUAN WUCHAPTER 9: The Role of Smart Data in Inference of Human Behavior and Interaction 191 – RUTE C. SOFIA, LILIANA CARVALHO, AND FRANCISCO M. PEREIRACHAPTER 10: Compression of Wearable Body Sensor Network Data 215 – ROBINSON RAJU, MELODY MOH, AND TENG-SHENG MOHCHAPTER 11: Population-Specific and Personalized (PSP) Models of Human Behavior for Leveraging Smart and Connected Data 243 – THEODORA CHASPARI, ADELA C. TIMMONS, AND GAYLA MARGOLINCHAPTER 12: Detecting Singular Data for Better Analysis of Emotional Tweets 259 – KIICHI TAGO, KENICHI ITO, AND QUN JINCHAPTER 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 LUNGUCHAPTER 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 BEGCHAPTER 15: When Big Data and Data Science Prefigured Ambient Intelligence 319 – CHRISTOPHE THOVEXCHAPTER 16: Ethical Issues and Considerations of Big Data 343 – EDWARD T. CHENCHAPTER 17: Data Protection by Design in Smart Data Environments 359 – PAOLO BALBONIINDEX, 391Reviews“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, ItalyAuthors BiographyKuan-Ching Li is a Distinguished Professor of Computer Science and Engineering at Providence University, Taiwan. He is a recipient of guest and distinguished chair professorships from universities in China and other countries, and awards and funding support from a number of agencies and industrial companies. He has been actively involved in many major conferences and workshops in program/general/steering conference chairman positions, and has organized numerous conferences related to highperformance computing and computational science and engineering. He is a Fellow of IET, senior member of the IEEE and a member of the AAAS, Editor-in-Chief of International Journal of Computational Science and Engineering (IJCSE), International Journal of Embedded Systems (IJES), and International Journal of High Performance Computing and Networking (IJHPCN), published by Inderscience. Besides publication of journal and conference research papers, he is co-author/co-editor of several technical professional books published by CRC Press, Springer, McGraw-Hill and IGI Global. His research interests include GPU/many-core computing, Big Data, and Cloud.Beniamino DiMartino is Full Professor at the University of Campania (Italy). He is author of 14 international books and more than 300 publications in international journals and conferences; has been Coordinator of EU funded FP7-ICT Project mOSAIC, and participates to various international research projects; is Editor / Associate Editor of seven international journals and EB Member of several international journals; is vice Chair of the Executive Board of the IEEE CS Technical Committee on Scalable Computing; is member of: IEEE WG for the IEEE P3203 Standard on Cloud Interoperability, IEEE Intercloud Testbed Initiative, IEEE Technical Committees on Scalable Computing (TCSC) and on Big Data (TCBD), Cloud Standards Customer Council, Cloud Computing Experts’ Group of the European Commission.Dr. Laurence T. Yang is a professor and W.F. James Research Chair at St. Francis Xavier University, Canada. His research includes parallel and distributed computing, embedded systems/internet of things, ubiquitous/pervasive computing and intelligence, and big data. He has published around 400 international journal papers in the above areas, of which half are on top IEEE/ACM Transactions and Journals, others ar mainly on Elsevier, Springer and Wiley Journals. He has been involved actively act as a steering chair for 10 IEEE international conferences. Now he is the chair of IEEE CS Technical Committee of Scalable Computing (2018-), the chair of IEEE SMC Technical Committee on Cybermatics (2016-). He is also serving as an editor for many international journals (such as IEEE Systems Journal, IEEE Access, Future Generation of Computer Systems (Elsevier), Information Sciences (Elsevier), Information Fusion (Elsevier), Big Data Research (Elsevier), etc). He is an elected fellow of Canadian Academy of Engineering (CAE) and Engineering Institute of Canada (EIC).Dr. Zhang is an Assistant Professor at St. Francis Xavier University, Canada. His research interests include big data, machine learning, and smart medicine. He has published more than 20 top international journal papers on the above topics including papers in IEEE Transactions on Computers, IEEE Transactions on Services Computing, ACM Multimedia Computing, Communications and Applications, and so on. He got an IEEE TCSC Award for Excellence in Scalable Computing for Early Career Researchers in 2018. He served as vice chair of IEEE Canada Atlantic Section CIS/SMC joint chapter (2018-2019). He served as a program chair of IEEE 14th International Conference on Pervasive, Intelligence and Computing (PICom 2016) and IEEE 11th International Conference on Internet of Things (iThings 2018). In addition, he is one of the guest editors of several international journals such as Future Generation Computer Systems, IEEE Access and Wireless Communication and Mobile Computing.