  Enterprises are investing heavily in cloud data centers to meet the ever
surging business demand. Data Center is a facility, which houses computer
systems and associated components, such as telecommunications and storage
systems. It generally includes power supply equipment, communication
connections and cooling equipment. A large data center can use as much
electricity as a small town. Due to the emergence of data center based
computing services, it has become necessary to examine how the costs associated
with data centers evolve over time, mainly in view of efficiency issues. We
have presented a quasi form of Cobb Douglas model, which addresses revenue and
profit issues in running large data centers. The stochastic form has been
introduced and explored along with the quasi Cobb Douglas model to understand
the behavior of the model in depth. Harrod neutrality and Solow neutrality are
incorporated in the model to identify the technological progress in cloud data
centers. This allows us to shed light on the stochastic uncertainty of cloud
data center operations. A general approach to optimizing the revenue cost of
data centers using Cobb Douglas Stochastic Frontier Analysis,CDSFA is
presented. Next, we develop the optimization model for large data centers. The
mathematical basis of CDSFA has been utilized for cost optimization and profit
maximization in data centers. The results are found to be quite useful in view
of production reorganization in large data centers around the world.
