NFV-VIPP:捕捉数据包处理的内部数据,加速nfv节点的发展和运营

Masahiro Dodare, Yuki Taguchi, Ryota Kawashima, Hiroki Nakayama, Tsunemasa Hayashi, H. Matsuo
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引用次数: 3

摘要

基于服务器的nfv节点具有不同的内部结构,例如同时部署虚拟网络功能(VNFs)和分层软件抽象(包括虚拟交换机)。针对功能硬件耦合设备量身定制的传统操作无法应对相关组件的增加和设备内部复杂的报文转发路径。此外,由于数据平面开发工具包(Data-Plane Development Kit, DPDK)对资源的独家管理,导致nfv内部节点无法进行精确的故障排除,吸引电信运营商的vnf自主开发仍然是一项非常复杂的工作。OPNFV晴雨表提供了统计数据采集的手段,但内部数据的分组处理仍然是公开的。在本文中,我们提出了一个专门针对nfv节点的集成度量收集框架(NFV-VIPP)。NFV-VIPP提供了对节点中系统组件的无缝理解,并通过透明地公开与实现相关的指标来揭示内部情况。NFV-VIPP可以通过RESTful api集成到Barometer/收集中,以增强系统可见性,这意味着我们的框架将nfv节点内部连接到现有的管理框架。我们使用NFVVIPP获得的内部vnf指标来探索nfv节点管理。具体来说,我们证明了接收间轮询的cpu周期消耗是估计系统负载的驱动力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
NFV-VIPP: Catching Internal Figures of Packet Processing for Accelerating Development and Operations of NFV-nodes
Server-based NFV-nodes have disparate internals, such as simultaneous deployment of Virtual Network Functions (VNFs) and layered software abstractions including a virtual switch. The traditional operations tailored for function-hardware-coupled devices cannot cope with the increase of related components as well as complicated packet forwarding paths inside. Besides, self-development of VNFs attracting Telcos is still highly complicated work, due to lack of exact troubleshooting of internal NFV-nodes caused by exclusive resource management by Data-Plane Development Kit (DPDK). OPNFV Barometer provides means of stats acquisition, but internal figures of packet processing are still unveiled. In this paper, we propose an integrated metrics collection framework (NFV-VIPP) specialized to NFV-nodes. NFV-VIPP provides seamless understandings of system components in a node, and reveals the inside by transparently exposing implementation-related metrics. NFV-VIPP can be incorporated into Barometer/collectd via RESTful APIs to reinforce system visibility, meaning that our framework bridges NFV-node internals to existing management frameworks. We explore NFV-node management using intra-VNF metrics obtained by NFVVIPP. Specifically, we prove that CPU-cycle consumption of inter-receive-polling is a driving force to estimate system load.
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