Machine Learning in the Cloud explores different machine learning techniques to solve problems in cloud management. Cloud computing offers subscription-based on-demand services, and it has emerged as the backbone of the computing industry. It has enabled us to share resources among multiple users through virtualization, which creates a virtual instance of a computer system running in an abstracted hardware layer. Unlike early distributed computing models, it offers virtually limitless computing resources through its large scale cloud data centers, and it has gained wide popularity over the past few years, with an ever-increasing infrastructure, number of users, and amount of hosted data. The large and complex workloads hosted on these data centers introduce many challenges, including resource utilization, power consumption, scalability, and operational cost. Therefore, an effective resource management scheme is essential to achieve operational efficiency with improved elasticity. Machine Learning for Cloud Management explores cloud resource management by the means of predictive modelling and virtual machine placement. The predictive approaches are developed using regression-based time series analysis and neural network models. The neural network-based models are primarily trained using evolutionary algorithms and the efficient virtual machine placement schemes are developed using multi-objective genetic algorithms. Key Features: the first book to set out a range of machine learning methods for efficient resource management in a large distributed network of clouds. predictive analytics are an integral part of efficient cloud resource management and this book gives a future research direction to researchers in this domain. it is written by leading international researchers. The book would be ideal for researchers who are working in the domain of cloud computing.

Book Information
ISBN 9780367622565
Author Jitendra Kumar
Format Paperback
Page Count 200
Imprint CRC Press
Publisher Taylor & Francis Ltd
Weight(grams) 156g