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.
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Cambazard, H., Mehta, D., O’Sullivan, B., Simonis, H. (2013). Constraint Programming Based Large Neighbourhood Search for Energy Minimisation in Data Centres. In: Altmann, J., Vanmechelen, K., Rana, O.F. (eds) Economics of Grids, Clouds, Systems, and Services. GECON 2013. Lecture Notes in Computer Science, vol 8193. Springer, Cham. https://doi.org/10.1007/978-3-319-02414-1_4
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DOI: https://doi.org/10.1007/978-3-319-02414-1_4
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