Energy Efficient NFV Orchestration using Machine Learning

“随着5G技术的发展，我们现在看到宽带、超可靠和零延迟服务的逐步实现。网络功能虚拟化（NFV）和移动边缘计算（MEC）是重要的5G元素，并且启用NFV的MEC网络允许虚拟网络功能（VNF）从远程云移动到边缘网络。与此同时，由于网络流量需求的快速增长和能源消耗问题的关注，能源效率要求有进一步提高的趋势。为了满足这些要求，我们将VNF的部署视为网络资源优化问题，旨在分配有限的CPU，内存和带宽，同时最大限度地减少ICT基础设施的网络能源足迹。"

"With the development of 5G technology, we now see the gradual realisation of broadband,ultra-reliable, and zero latency services. Network Function Virtualization (NFV) and MobileEdge Computing (MEC) are important 5G elements, and an NFV enabled MEC networkallows for movement of the Virtual Network Function (VNFs) from a distant cloud to an edgenetwork. At the same time, due to the rapid increment of network traffic demands and a focusof attention on energy consumption issues, there is a trend for much higher energyefficiency requirements. In order to satisfy such requirements we will consider thedeployment of VNFs as a network resource optimisation problem, aiming to allocate limited CPU, memory, and bandwidth while minimising the network-widew energy footprint of the ICT infrastructure."