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

## TL;DR

This paper presents an analytical framework for end-to-end performance analysis of service chaining in virtualized networks, incorporating MEC and core network servers, to aid in traffic management and system optimization.

## Contribution

It introduces a queueing and stochastic modeling approach for analyzing performance in service chaining scenarios with virtual network functions.

## Key findings

- Analytical and simulation results closely match.
- Performance metrics vary with different traffic and system configurations.
- Insights support traffic flow control decisions.

## Abstract

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 communications 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. Then, we show how to apply the similar method to an extended larger system and derive a stochastic model for such systems. We observe that the simulation and analytical results coincide. 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.