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Robust optimization for energy-efficient virtual machine consolidation in modern datacenters
2018
Cluster Computing
Energy efficient virtual machine (VM) consolidation in modern data centers is typically optimized using methods such as Mixed Integer Programming, which typically require precise input to the model. Unfortunately, many parameters are uncertain or very difficult to predict precisely in the real world. As a consequence, a once calculated solution may be highly infeasible in practice. In this paper, we use methods from robust optimization theory in order to quantify the impact of uncertainty in
doi:10.1007/s10586-018-2718-6
fatcat:43xms5t2vvgvjnt3zllc2jrov4