Multiobjective energy-aware datacenter planning accounting for power consumption profiles

Abstract

Energy efficiency is one of the major concerns when operating datacenters nowadays, as the large amount of energy used by parallel computing infrastructures impacts on both the energy cost and the electricity grid. Power consumption can be lowered by dynamically adjusting the power demand of datacenters, but conflicting objectives such as temperature and quality of service must be taken into account. This paper proposes a multiobjective evolutionary approach to solve the energyaware scheduling problem in datacenters, regarding power consumption, temperature, and quality of service when controlling servers and cooling infrastructures. Accurate results are reported for both best solutions regarding each of the problem objectives and best trade-off solutions.