NfvInsight: A Framework for Automatically Deploying and Benchmarking VNF Chains

doi:10.1007/s11390-020-0434-1

	NfvInsight: A Framework for Automatically Deploying and Benchmarking VNF Chains
	Xu, Tian-Ni 1,2; Sun, Hai-Feng 1,2; Zhang, Di 1,2; Zhou, Xiao-Ming 1,2; Sui, Xiu-Feng 3; Wang, Sa 1,2,4; Huang, Qun 5; Bao, Yun-Gang 1,2,4
	2022-06-01
发表期刊	JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY
ISSN	1000-9000
卷号	37 期号:3 页码:680-698
摘要	With the advent of virtualization techniques and software-defined networking (SDN), network function virtualization (NFV) shifts network functions (NFs) from hardware implementations to software appliances, between which exists a performance gap. How to narrow the gap is an essential issue of current NFV research. However, the cumbersomeness of deployment, the water pipe effect of virtual network function (VNF) chains, and the complexity of the system software stack together make it tough to figure out the cause of low performance in the NFV system. To pinpoint the NFV system performance issues, we propose NfvInsight, a framework for automatic deployment and benchmarking VNF chains. Our framework tackles the challenges in NFV performance analysis. The framework components include chain graph generation, automatic deployment, and fine granularity measurement. The design and implementation of each component have their advantages. To the best of our knowledge, we make the first attempt to collect rules forming a knowledge base for generating reasonable chain graphs. NfvInsight deploys the generated chain graphs automatically, which frees the network operators from executing at least 391 lines of bash commands for a single test. To diagnose the performance bottleneck, NfvInsight collects metrics from multiple layers of the software stack. Specifically, we collect the network stack latency distribution ingeniously, introducing only less than 2.2% overhead. We showcase the convenience and usability of NfvInsight in finding bottlenecks for both VNF chains and the underlying system. Leveraging our framework, we find several design flaws of the network stack, which are unsuitable for packet forwarding inside one single server under the NFV circumstance. Our optimization for these flaws gains at most 3x performance improvement.
关键词	network function virtualization (NFV) service chain performance bottleneck network stack latency
DOI	10.1007/s11390-020-0434-1
收录类别	SCI
语种	英语
资助项目	National Key Research and Development Program of China[2019YFB1802600] ; National Natural Science Foundation of China[61420106013] ; National Natural Science Foundation of China[61702480] ; National Natural Science Foundation of China[61672499] ; National Natural Science Foundation of China[61802365] ; Youth Innovation Promotion Association of Chinese Academy of Sciences[2013073] ; Youth Innovation Promotion Association of Chinese Academy of Sciences[2020105] ; Guangdong Province Key Laboratory of Popular High Performance Computers[2017B030314073]
WOS研究方向	Computer Science
WOS类目	Computer Science, Hardware & Architecture ; Computer Science, Software Engineering
WOS记录号	WOS:000812520400014
出版者	SCIENCE PRESS
引用统计
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/19525
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Bao, Yun-Gang
作者单位	1.Chinese Acad Sci, Inst Comp Technol, State Key Lab Comp Architecture, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 3.Beijing Inst Technol, Sch Informat & Elect, Beijing 100081, Peoples R China 4.Peng Cheng Lab, Shenzhen 518055, Peoples R China 5.Peking Univ, Dept Comp Sci & Technol, Beijing 100871, Peoples R China
推荐引用方式 GB/T 7714	Xu, Tian-Ni,Sun, Hai-Feng,Zhang, Di,et al. NfvInsight: A Framework for Automatically Deploying and Benchmarking VNF Chains[J]. JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY,2022,37(3):680-698.
APA	Xu, Tian-Ni.,Sun, Hai-Feng.,Zhang, Di.,Zhou, Xiao-Ming.,Sui, Xiu-Feng.,...&Bao, Yun-Gang.(2022).NfvInsight: A Framework for Automatically Deploying and Benchmarking VNF Chains.JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY,37(3),680-698.
MLA	Xu, Tian-Ni,et al."NfvInsight: A Framework for Automatically Deploying and Benchmarking VNF Chains".JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY 37.3(2022):680-698.