Fog computing is an emerging paradigm that aims to improve the efficiency and QoS of cloud computing by extending the cloud to the edge of the network. This paper develops a comprehensive energy efficiency analysis framework based on mathematical modeling and heuristics to study the offloading of virtual machine (VM) services from the cloud to the fog. The analysis addresses the impact of different factors including the traffic between the VM and its users, the VM workload, the workload versus number of users profile and the proximity of fog nodes to users. Overall, the power consumption can be reduced if the VM users traffic is high and/or the VMs have a linear power profile. In such a linear profile case, the creation of multiple VM replicas does not increase the computing power consumption significantly (there may be a slight increase due to idle / baseline power consumption) if the number of users remains constant, however the VM replicas can be brought closer to the end users, thus reducing the transport network power consumption. In our scenario, the optimum placement of VMs over a cloud-fog architecture significantly decreased the total power consumption by 56% and 64% under high user data rates compared to optimized distributed clouds placement and placement in the existing AT&T network cloud locations, respectively.

中文翻译：

---

云雾网络架构上的节能虚拟机放置

雾计算是一种新兴范式，旨在通过将云扩展到网络边缘来提高云计算的效率和 QoS。本文开发了一个基于数学建模和启发式的综合能效分析框架，以研究虚拟机 (VM) 服务从云到雾的卸载。该分析解决了不同因素的影响，包括 VM 与其用户之间的流量、VM 工作负载、工作负载与用户配置文件的数量以及雾节点与用户的接近程度。总的来说，如果 VM 用户流量很高和/或 VM 具有线性功率分布，则可以降低功耗。在这样的线性剖面情况下，如果用户数量保持不变，创建多个VM副本不会显着增加计算功耗（由于空闲/基线功耗可能会略有增加），但是可以使VM副本更接近最终用户，从而降低传输网络功耗。在我们的场景中，与优化的分布式云放置和现有 AT&T 网络云位置中的放置相比，在云雾架构上虚拟机的最佳放置在高用户数据速率下显着降低了 56% 和 64% 的总功耗。