A university project is underway that works upon the principle of performance-based allocation of resources rather than reservation-based allocation of resources, as is done in existing technologies. In terms of real costs, this will reduce operations and capital expenditures for the purchase of larger capacity servers found in data centers, when compared to the use of cloud-based resources.

The tool is called “Quasar.”  On March 1, 2014, in Salt Lake City, CA, Quasar will be presented to the industries to question and assess the implementation of the software.  The project is completed by two students – Christos Kozyrakis and Christina Delimitrou.  Christos is an associate professor, electrical engineering and computer science, while Christina is a doctoral student at Stanford University.

These types of projects will help enterprises understand the true value of leveraging cloud computing.  While the providers have similar tools, they are not an objective third party.  The use of “Quasar,” if it lives up to expectations, could be leveraged by most enterprises to help consider the cost effectiveness of cloud computing.