  The energy consumption of Data Centers (DCs) is a very important figure for
the telecommunications operators, not only in terms of cost, but also in terms
of operational reliability. A relation between the energy consumption and the
weather conditions would indicate that weather forecast models could be used
for predicting energy consumption of DCs. A reliable forecast would result in a
more efficient management of the available energy and would make it easier to
take advantage of the modern types of power-grid based on renewable energy
resources. In this ,paper, we exploit the capabilities provided by the
FIESTA-IoT platform in order to investigate the correlation between the weather
conditions and the energy consumption in DCs. Then, by using multi-variable
linear regression process, we model this correlation between the energy
consumption and the dominant weather conditions parameters in order to
effectively forecast the energy consumption based on the weather forecast. We
have validated our results through live measurements from the RealDC testbed.
Results from our proposed approach indicate that forecasting of energy
consumption based on weather conditions could help not only DC operators in
managing their cooling systems and power usage, but also electricity companies
in optimizing their power distribution systems.
