This book features a collection of high-quality research papers presented at the International Conference on Intelligent and Cloud Computing (ICICC 2019), held at Siksha 'O' Anusandhan (Deemed to be University), Bhubaneswar, India, on December 20, 2019. Including contributions on system and network design that can support existing and future applications and services, it covers topics such as cloud computing system and network design, optimization for cloud computing, networking, and applications, green cloud system design, cloud storage design and networking, storage security, cloud system models, big data storage, intra-cloud computing, mobile cloud system design, real-time resource reporting and monitoring for cloud management, machine learning, data mining for cloud computing, data-driven methodology and architecture, and networking for machine learning systems.

Autorentext
Prof. (Dr.) Debahuti Mishra received her B.E. degree in Computer Science and Engineering from Utkal University, Bhubaneswar, India, in 1994; her M.Tech. degree in Computer Science and Engineering from KIIT Deemed to be University, Bhubaneswar, India, in 2006; and her Ph.D. degree in Computer Science and Engineering from Siksha 'O' Anusandhan Deemed to be University, Bhubaneswar, India, in 2011. She is currently working as a Professor and Head of the Department of Computer Science and Engineering, at the same university.
Dr. Rajkumar Buyya is a Redmond Barry Distinguished Professor and Director of the Cloud Computing and Distributed Systems (CLOUDS) Laboratory at the University of Melbourne, Australia. He is also the founding CEO of Manjrasoft, a spin-off company that commercializes university innovations in cloud computing. He served as a Future Fellow of the Australian Research Council from 2012 to 2016. He has authored over 625 publications and seven textbooks, including Mastering Cloud Computing, published by McGraw Hill, China Machine Press, and Morgan Kaufmann for Indian, Chinese and international markets, respectively.
Dr. Prasant Mohapatra is the Vice Chancellor for Research at the University of California, Davis. He is also a Professor at the Department of Computer Science and served as the Dean and Vice-Provost of Graduate Studies at the University of California, Davis, from 2016 to 18. He was also an Associate Chancellor in 201416, and the Interim Vice-Provost and CIO of UC Davis in 201314. Further, he was the Department Chair of Computer Science from 2007 to 13 and held the Tim Bucher Family Endowed Chair Professorship during that period. He has also been a member of the faculty at Iowa State University and Michigan State University.
Dr. Srikanta Patnaik is a Professor at the Department of Computer Science and Engineering, Faculty of Engineering and Technology, SOA University, Bhubaneswar, India. Dr. Patnaik has published 100 research papers in international journals and conference proceedings. Dr. Patnaik is the Editor-in-Chief of the International Journal of Information and Communication Technology and International Journal of Computational Vision and Robotics, published by Inderscience Publishing House, England, and also Editor-in-Chief of a book series on Modeling and Optimization in Science and Technology, published by Springer, Germany.

Inhalt
Part 1: An energy efficient data routing in weight-balanced tree-based Fog Network.- A Systematic Overview of Fault Tolerance In Cloud Computing.- An EPIC Mechanism for Advertising the Tourist Spots in Smart Cities.- Data Analysis and Prediction of Terror Component Using Web Services.- Issues, Challenges and Techniques for Resource Provisioning in Cloud Computing Environment.- Load Balancing of Tasks in Cloud Computing using Fault Tolerant Honey Bee Foraging Approach.- Flip Learning: A Novel IoT Based Learning Initiative.- Improvement of Load Balancing in Shared Memory Multiprocessor Systems.- Building Amazon Web Services Infrastructure from the scratch for an Organisation.- Fault Detection for VANET using Vehicular Cloud.- An approach to Cohort Selection in Cloud for Face Recognition.- Internet of Things (IoT) framework Deployment Template for Cloud-based Harbor Surveillance and Ferry Monitoring System.- Art of Style Transfer using Convolution Neural Network: A deep learning approach.- The Impact of IoT on 5G.- Prediction of Exchange Rate in a Cloud Computing Environment Using Machine Learning Tools.- Survey on Stock Price Forecasting using Regression Analysis.- Intrusion Detection and classification using decision tree based feature selection classifiers.- Role of Cloud Computing for Big Data: A review.- Role of cloud computing in geotechnical engineering.- Energy Efficient Clustering with Rotational Supporter in Wireless Sensor Network.- Mobile Cloud Computing: - A Case Study.- Corroborating the Veracity of Body Fat Percentage using Residuals and Goodness-of-Fit.- Design of Compact Super-Wideband Monopole Antenna for Spectrum Sensing Applications.- Probabilistic and Distance-Aware Clustering Approach to Decrease the Effect of Hot-Spot in WSN.- A Real-Time Sentiments Analysis System using Twitter Data.- Low Profile Circularly Polarized Antenna for Contemporary Wireless Communication Applications.- Detection of XSS Vulnerabilities of Web Application Using Security Testing Approaches.- Part II: Evolutionary Hybrid Feature Selection for Cancer Diagnosis.- Predicting the Price of Gold: A CSPNN-DE Model.- Weighted Particle Swarm Optimization with t-distribution in Machine Learning Applications.- A novel approach for breast cancer classification using Deep forest network.- A Survey on Deep Learning: Convolution Neural Network.- An Optimized Method for Arrhythmia Classification using Artificial Neural Network.- A Survey on Hybridized Gene Selection Strategies.- Indian Stock Market Prediction based on Rough Set and Support Vector Machine Approach.- Epileptic Seizure Detection Using DWT and Rule Based Variants of TSVM with KNN.- Artificial Intelligence for Smart-Healthcare Management: Brief Study.- Leaves Shape Categorization using Convolution Neural Network Model.- Thyroid Disorder Analysis Using Random Forest Classifier.- Global Best Guided Modified Cat Swarm Optimization Algorithm for Applications in Machine Learning.