New pricing policies are emerging where cloud providers charge resource provisioning based on the allocated CPU frequencies. As a result, resources are offered to users as combinations of different performance levels and prices which can be configured at runtime. With such new pricing schemes and the increasing energy costs in data centres, balancing energy savings with performance and revenue losses is a challenging problem for cloud providers. CPU frequency scaling can be used to reduce power dissipation, but also impacts virtual machine (VM) performance and therefore revenue. In this paper, we first propose a non-linear power model that estimates power dissipation of a multi-core CPU physical machine (PM) and second a pricing model that adjusts the pricing based on the VM's CPU-boundedness characteristics. Finally, we present a cloud controller that uses these models to allocate VM and scale CPU frequencies of the physical machine (PM) to achieve energy cost savings that exceed service revenue losses. We evaluate the proposed approach using simulations with realistic VM workloads, electricity price and temperature traces and estimate energy savings of up to 14.57 percent.

中文翻译：

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多核地理分布式云计算中基于性能的定价

新的定价政策正在出现，云提供商根据分配的 CPU 频率对资源配置收费。因此，资源作为可以在运行时配置的不同性能级别和价格的组合提供给用户。随着这些新的定价方案和数据中心能源成本的增加，平衡节能与性能和收入损失对云提供商来说是一个具有挑战性的问题。CPU 频率调整可用于降低功耗，但也会影响虚拟机 (VM) 性能，从而影响收入。在本文中，我们首先提出了一个非线性功耗模型，用于估计多核 CPU 物理机 (PM) 的功耗，然后提出一个定价模型，该模型根据 VM 的 CPU 有界特性调整定价。最后，我们提出了一个云控制器，它使用这些模型来分配 VM 并扩展物理机 (PM) 的 CPU 频率，以实现超过服务收入损失的能源成本节约。我们使用具有真实 VM 工作负载、电价和温度跟踪的模拟来评估提议的方法，并估计最多可节省 14.57% 的能源。