Thermal-aware cloud middleware to reduce cooling needs

As we are living in a data-driven world and directed toward internet, the need for data enter is growing. The main limitation for building cloud infrastructures is their energy consumption. Moreover, their conception is not perfect because servers are not the ones consuming all the power, cooling systems are responsible for half of the consumption. Cooling costs can be reduced by intelligent scheduling, and in our case through virtual machines migrations. In this paper, we propose a dynamic reconfiguration based on evolution of temperatures and load of the servers. The idea is to share heat production to reduce cooling costs and consolidate the workload when possible to reduce servers costs. The challenge resides in satisfying these opposite objectives. We tested our algorithm on an experimental test bed, and achieve to cap the temperature of the data enter room while not forgetting to optimize the server use, and without impacting on applications performance