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 with dynamic pricing and propose a novel online algorithm, called CAPRI (CApacity provisioning and PRIcing), to maximize the profit of a data center while satisfying the energy capping constraint. We prove that CAPRI achieves a close-to-maximum profit 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 CAPRI. © 2013 IEEE.
CApacity provisioning and PRIcing for cloud computing with energy capping / Polverini, Marco; Shaolei, Ren; Cianfrani, Antonio. - ELETTRONICO. - (2013), pp. 413-420. (Intervento presentato al convegno 51st Annual Allerton Conference on Communication, Control, and Computing, Allerton 2013 tenutosi a Monticello, IL nel 2 October 2013 through 4 October 2013) [10.1109/allerton.2013.6736554].
CApacity provisioning and PRIcing for cloud computing with energy capping
POLVERINI, MARCO;CIANFRANI, Antonio
2013
Abstract
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 with dynamic pricing and propose a novel online algorithm, called CAPRI (CApacity provisioning and PRIcing), to maximize the profit of a data center while satisfying the energy capping constraint. We prove that CAPRI achieves a close-to-maximum profit 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 CAPRI. © 2013 IEEE.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.