Online Resource Management for Data Center with Energy Capping

The past few years have been witnessing a surging demand for cloud computing services, resulting in a huge carbon footprint and making energy cost one of the top operational costs of data centers. Meanwhile, as sustainable computing has become increasingly important, data centers are constantly pressured to cap the long-term usage of their energy produced from carbon-intensive sources (a.k.a., “brown” energy). In this paper, we study energy budgeting and propose a novel online resource management algorithm, called ORM, to control the number of active servers for delaysensitive workloads in a data center for minimizing the operational cost while satisfying the energy capping constraint. We rigorously prove that ORM achieves a close-tominimum operational cost compared to the optimal offline algorithm with future information, while bounding the potential violation of energy capping, in an almost arbitrarily random environment. We also perform a trace-based simulation study to complement the analysis and validate the effectiveness of ORM.