基于实验数据分析的CPU利用的能量有效的SDN和SDR联合自适应
Energy Efficient SDN and SDR Joint Adaptation of CPU Utilization Based on Experimental Data Analytics
摘要：
在本文中，我们提出了一种混合软件架构的网络功能虚拟化（NFV），其中软件定义网络（SDN）和软件定义无线电（SDR）组件集成，形成一个基于云的通信系统。我们分析了OpenIreland测试平台中不同参数设置和NFV架构用例场景的CPU利用率和功耗。实验结果显示了SDN数据平面交换和SDR在CPU利用率和并行化方面的不同行为，这为将它们集成到基于云的系统中时的处理聚合和节能提供了见解。然后，我们提出了一个节能方案，灵活的CPU分配，可以降低系统的整体功耗。我们的结果表明，与单独部署SDN和SDR的传统方案相比，我们提出的NFV架构及其节能方案可以节省高达20%的功耗。
英文摘要：
In this paper we propose a hybrid softwarized architecture of Network Function Virtualization (NFV) where Software-Defined Networking (SDN) and Software-Defined Radio (SDR) components are integrated to form a cloud-based communication system. We analyze CPU utilization and power consumption in the OpenIreland testbed for different parameter settings and use case scenarios of this NFV architecture. The experiment results show different behaviour between SDN data plane switching and SDR in terms of CPU utilization and parallelization, which provides insights for processing aggregation and power savings when integrating them together in a cloud-based system. We then propose a power saving scheme with flexible CPU allocation that can reduce the overall power consumption of the system. Our results show that our proposed NFV architecture and its power saving scheme can save up to 20% power consumption compared to conventional scheme where SDN and SDR are separately deployed.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
