Capping the electricity cost of cloud-scale data centers with impacts on power markets

Yanwei Zhang, Yefu Wang, Xiaorui Wang
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引用次数: 40

Abstract

In this paper, we propose a novel electricity cost capping algorithm that not only minimizes the electricity cost of operating cloud-scale data centers, but also enforces a cost budget on the monthly electricity bill. Our solution first explicitly models the impacts of power demands on electricity prices and the power consumption of cooling and networking in the minimization of electricity cost. In the second step, if the electricity cost exceeds a desired monthly budget due to unexpectedly high workloads, our solution guarantees the quality of service for premium customers and trades off the request throughput of ordinary customers. We formulate electricity cost capping as two related constrained optimization problems and propose an efficient algorithm based on mixed integer programming. Simulation results show that our solution outperforms the state-of-the-art solutions by having lower electricity costs and achieves desired cost capping with maximized request throughput.
限制云规模数据中心的电力成本,并对电力市场产生影响
在本文中,我们提出了一种新的电力成本上限算法,该算法不仅可以最大限度地降低运营云规模数据中心的电力成本,而且还可以对每月的电费账单进行成本预算。我们的解决方案首先明确地模拟了电力需求对电价的影响,以及在电力成本最小化的情况下冷却和联网的电力消耗。在第二步中,如果由于意外的高工作负载导致电力成本超过预期的每月预算,我们的解决方案将保证高级客户的服务质量,并权衡普通客户的请求吞吐量。我们将电费上限问题表述为两个相关的约束优化问题,并提出了一种基于混合整数规划的高效算法。仿真结果表明,我们的解决方案具有较低的电力成本,并以最大的请求吞吐量实现所需的成本上限,从而优于当前最先进的解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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