An End-to-End Performance Analysis for Service Chaining in a Virtualized Network

被引:10
作者
Fountoulakis, Emmanouil [1 ]
Liao, Qi [2 ]
Pappas, Nikolaos [1 ]
机构
[1] Linkoping Univ, Dept Sci & Technol, S-60174 Norrkoping, Sweden
[2] Nokia Bell Labs, End End Network & Serv Automat Lab, D-70435 Stuttgart, Germany
来源
IEEE OPEN JOURNAL OF THE COMMUNICATIONS SOCIETY | 2020年 / 1卷
基金
欧盟地平线“2020”;
关键词
Applied queueing theory; delay analysis; end-to-end performance analysis; multi-access edge computing; network function virtualization; throughput analysis; STABILITY;
D O I
10.1109/OJCOMS.2020.2966689
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Future mobile networks supporting Internet of Things are expected to provide both high throughput and low latency to user-specific services. One way to overcome this challenge is to adopt Network Function Virtualization (NFV) and Multi-access Edge Computing (MEC). Besides latency constraints, these services may have strict function chaining requirements. The distribution of network functions over different hosts and more flexible routing caused by service function chaining raise new challenges for end-to-end performance analysis. In this paper, as a first step, we analyze an end-to-end communication system that consists of both MEC servers and a server at the core network hosting different types of virtual network functions. We develop a queueing model for the performance analysis of the system consisting of both processing and transmission flows. We propose a method in order to derive analytical expressions of the performance metrics of interest, i.e., end-to-end delay, system throughput, task drop rate. Then, we show how to apply the similar method to a larger system and derive a stochastic model for such systems. We observe that the simulation and analytical results are very close. By evaluating the system under different scenarios, we provide insights for the decision making on traffic flow control and its impact on critical performance metrics.
引用
收藏
页码:148 / 163
页数:16
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