Exploring Mobility and Scalability of Cloud Computing Servers Using Logical Regression Framework

This research paper explores the possibilities of using the Logical Regression Framework as a means of controlling the scalability and mobility of cloud computing servers. The aim of this research paper is to identify the key factors that serve as predictors of good scalability and mobility performance in cloud computing servers. In doing so, the research undertakes a comparative analysis of different cloud computing architectures in order to identify which architectures exhibit better scalability and mobility performance. This comparative evaluation is done through the use of a Logical Regression Framework, which is based on two main data sources: (1) the server performance logs and (2) the server utilization rate. Each of these datasets is explored in depth to find correlations between certain features and scalability/mobility performance. Using this information, an optimal cloud architecture is determined that shows better scalability and mobility characteristics. The hope is that this research can help cloud computing architects and engineers to design and implement better architectures for their cloud-based applications.