Abstract
EnergeTIC is a recent industrial research project carried out in Grenoble on optimizing energy consumption in data-centres. The efficient management of a data-centre involves minimizing energy costs while ensuring service quality. We study the problem formulation proposed by EnergeTIC. First, we focus on a key sub-problem: a bin packing problem with linear costs associated with the use of bins. We study lower bounds based on Linear Programming and extend the bin packing global constraint with cost information. Second, we present a column generation model for computing the lower bound on the original energy management problem where the pricing problem is essentially a cost-aware bin packing with side constraints. Third, we show that the industrial benchmark provided so far can be solved to near optimality using a large neighborhood search.
The authors acknowledge their industrial partners (Bull, Schneider Electric, Business & Decision and UXP) as well as several public research institutions (G2Elab, G-SCOP and LIG). The authors from UCC are supported by Science Foundation Ireland Grant No. 10/IN.1/I3032.
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References
A framework for data center energy productivity. Technical report, The green grid (2008)
Efficience des Data Centers, les retombées du projet EnergeTIC. Technical report (2013), http://www.vesta-system.cades-solutions.com/images/vestalis/4/energetic_white%20paper.pdf
Anily, S., Bramel, J., Simchi-Levi, D.: Worst-case analysis of heuristics for the bin packing problem with general cost structures. Operational Research 42 (1994)
Baldi, M.M., Crainic, T.G., Perboli, G., Tadei, R.: The generalized bin packing problem. Transportation Research Part E: Logistics and Transportation Review 48(6), 1205–1220 (2012)
Crainic, T.G., Perboli, G., Rei, W., Tadei, R.: Efficient lower bounds and heuristics for the variable cost and size bin packing problem. Comput. Oper. Res. 38(11), 1474–1482 (2011)
de Carvalho, J.M.V.: Exact solution of bin packing problems using column generation and branch-and-bound. Annals of Operations Research 86(0), 629–659 (1999)
de Carvalho, J.M.V.: LP models for bin packing and cutting stock problems. European Journal of Operational Research 141(2), 253–273 (2002)
Dupont, C., Schulze, T., Giuliani, G., Somov, A., Hermenier, F.: An energy aware framework for virtual machine placement in cloud federated data centres. In: Proceedings of the 3rd International Conference on Future Energy Systems: Where Energy, Computing and Communication Meet, e-Energy 2012, pp. 4:1–4:10. ACM, New York (2012)
Epstein, L., Levin, A.: Bin packing with general cost structures. Math. Program. 132(1-2), 355–391 (2012)
Gilmore, P.C., Gomory, R.E.: A linear programming approach to the cutting-stock problem. Operations research 11, 863–888 (1963)
Haouari, M., Serairi, M.: Relaxations and exact solution of the variable sized bin packing problem. Comput. Optim. Appl. 48(2), 345–368 (2011)
Li, C.L., Chen, Z.L.: Bin-packing problem with concave costs of bin utilization. Naval Research Logistics 53, 298–308 (2006)
Martello, S., Toth, P.: Lower bounds and reduction procedures for the bin packing problem. Discrete Applied Mathematics 28(1), 59–70 (1990)
Mehta, D., O’Sullivan, B., Simonis, H.: Comparing solution methods for the machine reassignment problem. In: Milano, M. (ed.) CP 2012. LNCS, vol. 7514, pp. 782–797. Springer, Heidelberg (2012)
Monaci, M.: Algorithms for Packing and Scheduling Problems. PhD thesis, Universit di Bologna (2012)
Petrucci, V., Loques, O., Mosse, D.: A dynamic configuration model for power-efficient virtualized server clusters. In: Proceedings of the 11th Brazilian Workshop on Real-Time and Embedded Systems (2009)
Rothvoss, T.: Approximating bin packing within \(\mathcal{O}\)(logOPT·loglogOPT) bins. Technical report, MIT (2013)
Salvagnin, D.: Orbital shrinking: A new tool for hybrid MIP/CP methods. In: Gomes, C., Sellmann, M. (eds.) CPAIOR 2013. LNCS, vol. 7874, pp. 204–215. Springer, Heidelberg (2013)
Shaw, P.: A constraint for bin packing. In: Wallace, M. (ed.) CP 2004. LNCS, vol. 3258, pp. 648–662. Springer, Heidelberg (2004)
Srikantaiah, S., Kansal, A., Zhao, F.: Energy aware consolidation for cloud computing. In: Proceedings of HotPower (2008)
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Cambazard, H., Mehta, D., O’Sullivan, B., Simonis, H. (2013). Bin Packing with Linear Usage Costs – An Application to Energy Management in Data Centres. In: Schulte, C. (eds) Principles and Practice of Constraint Programming. CP 2013. Lecture Notes in Computer Science, vol 8124. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40627-0_7
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DOI: https://doi.org/10.1007/978-3-642-40627-0_7
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