Abstract
In recent years, because of the increase in the huge volume of data and increase in data analytics in various research areas like health care, image processing etc., it is highly needed to provide required resources for processing the information. Cloud computing process an approach for delivering required resources by improving the utilization of data-center resources which results in increasing the energy costs. In order to overcome this new energy-efficient algorithms are introduced, that decreases the overall energy consumption of computation and storage. To reduce the energy-efficiency in cloud data centers, server consolidation technique is used, which plays a major road block. To address this issue, this project proposes a Prediction based Thermal Aware Server Consolidation (PTASC) model, a consolidation method, which takes numeric and local architecture into consideration along with Service Level Agreement. PTASC, consolidates servers (VM Migration) using a statistical learning method.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call