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. © 2013 Springer International Publishing.
CITATION STYLE
Cambazard, H., Mehta, D., O’Sullivan, B., & Simonis, H. (2013). Constraint programming based large neighbourhood search for energy minimisation in data centres. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8193 LNCS, pp. 44–59). https://doi.org/10.1007/978-3-319-02414-1_4
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