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Optimizing cooling and server power consumption

机译:优化散热和服务器功耗

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This paper proposes new solution strategies for a challenging optimization problem, called Cooling-aware Workload Placement Problem, that looks for a workload placement that optimizes the overall data center power consumption given by the sum of the server power consumption and of the computer room air conditioner power consumption. We formulate CWPP as a Mixed Integer Non Linear Problem using a cross-interference matrix that links the workload placement to the cold air temperature. Since state-of-the-art Mixed Integer Non Linear solvers can solve to optimality only the smallest instances, we devised two heuristics to obtain good feasible solutions: (i) a heuristic algorithm based on an integer linear relaxation of the problem, and (ii) a Variable Neighborhood Search algorithm. Both heuristic algorithms are evaluated against the best lower bounds obtained with a Mixed Integer Non Linear solver. Computational results show that both heuristics provide solutions that have a small percentage gap from the optimal solutions.
机译:本文针对具有挑战性的优化问题提出了新的解决方案策略,称为制冷意识的工作负载放置问题,该问题寻找一种工作负载放置,该工作负载放置可以通过服务器功耗和计算机房空调的总和来优化总体数据中心的功耗。能量消耗。我们使用交叉干扰矩阵将CWPP公式化为混合整数非线性问题,该矩阵将工作负荷位置与冷空气温度联系起来。由于最新的混合整数非线性求解器只能求解最小实例的最优性,因此我们设计了两种启发式方法以获得良好的可行解:(i)一种基于整数线性松弛问题的启发式算法,以及( ii)可变邻域搜索算法。两种启发式算法均针对使用混合整数非线性求解器获得的最佳下限进行了评估。计算结果表明,两种启发式方法都提供了与最佳解决方案相差很小百分比的解决方案。

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