Expansion of Data Centers’ Energetic Degrees of Freedom to Employ Green Energy Sources

Rising power consumption of data centers is a topic of great concern and therefore several power saving technologies exist. This paper describes the idea of a data center overall power saving and controlling strategy, allowing the data center to enter optimized minimum power states while still keeping up flexibility but also to control its own power consumption to apply demand response management. Therefore, the degrees of freedom a virtualized data center has are modeled and the methodology used to control its energy state is described, taking into account the IT hardware like servers and network gear as well as the influence of cooling devices and power distribution devices. This knowledge can also be used to react to data center emergencies like cooling failures. We describe our simulation models, the methodology and the power saving potential of our system. We formulate the problem to control the data center’s power consumption by applying different consolidation strategies as an extended bin packing optimization problem, where virtual machines must be packed on a specific number of servers. External constraints like the time-flexibility of the solution and the influence on supporting devices are applied by using cost functions. We present a solving approach for this problem in the form of the data center multi-criteria aware allocation heuristic DaMucA and compare it to the traditional first fit decreasing heuristic.