Microservices in Big Data Analytics
Description
These proceedings gather cutting-edge papers exploring the principles, techniques, and applications of Microservices in Big Data Analytics.
The ICETCE-2019 is the latest installment in a successful series of annual conferences that began in 2011. Every year since, it has significantly contributed to the research community in the form of numerous high-quality research papers. This year, the conference's focus was on the highly relevant area of Microservices in Big Data Analytics.
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Persons
Dr. Anil Chaudhary is Professor in the Department of Information Technology at the Swami Keshvanand Institute of Technology. Dr. Chaudhary received Ph.D. in Computer Science Engineering, M.Phil. in Computer Science, M.Tech. in Computer Science, & M.Sc. in Mathematics. He brings with him years of rich experience in Distributed Systems, Enterprise Software Development, Deep Learning in Education, Mobile Application Development, Software Engineering & Modeling. He has published a number of papers in reputed conferences and journals.
Dr. Chothmal Choudhary
is currently a Professor in the Department of Computer Science and Engineering at the Swami Keshvanand Institute of Technology, Jaipur. He has vast teaching and industry experience. His current research interests include architectural modeling of web applications and machine learning techniques. He has also published several books and articles with reputed publishers.
Dr. Chhagan Lal
is a postdoc research fellow in the Department of Mathematics at University of Padua, Italy, and an Affiliate Associate Professor at the Manipal University Jaipur, India. He obtained Ph.D. in Computer Science and Engineering from Malaviya National Institute of Technology, Jaipur, India, in 2014, and master's in Information Technology with specialization in "Wireless communication" from Indian Institute of Information Technology, Allahabad, in 2009. His current research areas include blockchain analysis, security in wireless networks, software-defined networking, underwater acoustic networks, and context-based security solutions for Internet of Things (IoT) networks. In this area, he published more than 30 papers in topmost international peer-reviewed journals and conference.
Dr. Mukesh Kumar Gupta
is currently working as an Associate Professor in the Department of Computer Science and Engineering at the Swami Keshvanand Institute of Technology, Jaipur, where he joined as a lecturer in 2002. Dr. Gupta received B.E. degree in Computer Science and Engineering from Government Engineering College, Kota, in 1999; M.Tech. from IIT Bombay and Ph.D. from MNIT Jaipur, in 2008 and 2016, respectively.
His current research interests include security of web applications using machine learning techniques and modeling of web applications. Dr. Gupta is a Member of Standing Executive Board (SEB) in Software Technology Parks (STPI) of India, Jaipur; Member Board of Governors, Swami Keshvanand Institute of Technology, Management & Gramothan, Jaipur; Member of IEEE and IEEE Computer Society. He is a Life Member of the Indian Society for Technical Education (ISTE).
Content
Adaptive VM Migration and Allocation Mechanism in Cloud Environment.- Educational Cloud Framework-A Literature Review on Finding Better Private Cloud Framework for Educational Hub.- Improved DYMO Based ACO for MANET Using Distance and Density of Nodes.- An Efficient ATM Surveillance Framework Using Optical Flow with CNN.- An Efficient Approach for Image Encryption using Zigzag, Arnold Transformation and Double Random Phase Encoding in Fractional Fourier Transform Domain.- Comparison of Execution Time of Mobile Application Using Equal Division and Profile Based algorithm in Mobile Cloud Computing.- Ontological Design of Information Retrieval Model for Real Estate Documents.- Parameter Optimization in Convolutional Neural Networks Using Gradient Descent.- Empirical Investigation of Usability Evaluation Methods for Mobile Applications Using Evidence Based Approach.- Prediction of Underwater Surface Target through SONAR: A Case Study of Machine Learning.- Big Data Machine Learning Framework for Drug Toxicity Prediction.- Implementation of Block Based Symmetric Algorithms for Real Image Encryption.- Human Emotion Recognition Using Body Expressive Feature.- Self-Energizing Wireless Sensor Network.- A Fuzzy Logic Based Control System for Detection and Mitigation of Black Hole Attack in Vehicular Ad-Hoc Network.- Cloud Computing Based Approach for Accessing Electronic Health Record for Healthcare Sector.
