Constraint Programming Based Large Neighbourhood Search for Energy Minimisation in Data Centres

Abstract

Abstract. EnergeTIC is a recent industrial research project carried out in Grenoble on optimising energy consumption in data centres. We study the problem formulation proposed by EnergeTIC. The problem focuses on the allocation of virtual machines to servers with time-variable resource demands in data centres in order to minimise energy costs while ensuring service quality. We present a scalable constraint programming-based large neighbourhood search (CP-LNS) method to solving this challenging problem. We present empirical results that demonstrate that the industrial benchmarks can be solved to near optimality using our approach. Our CP-LNS method provides a fast and practical approach for finding high quality solutions for lowering electricity costs in data centres.

Machine reassignment problem: the ROADEF/EURO challenge 2012

“…They propose a dynamic round-robin algorithm, for energy-aware virtual machine scheduling and consolidation. Cambazard et al (2013) address the allocation of virtual machines to servers with time-variable resource demands in data centers in order to minimize energy costs while ensuring service quality. They present a scalable constraint programming-based large neighborhood search method.…”