Controlling datacenter power consumption while maintaining temperature and QoS levels

The large amount of energy used by datacenters impacts both energy cost and the electricity grid. These issues can be mitigated by dynamically adjusting the power demand of datacenters. However, conflicting objectives have to be considered: workload and cooling can be dynamically reduced, but with a potential impact on quality of service or excursions beyond acceptable temperature bands. In this paper we use a multi-objective evolutionary algorithm to explore the trade-offs between power consumption, temperature, and quality of service when both servers and cooling are controlled holistically in a datacenter.