@article{M913DA503,
title = "Performance Evaluation and Analysis on Single and Multi-Network Virtualization Systems with Virtio and SR-IOV",
journal = "The Transactions of the Korea Information Processing Society",
year = "2024",
issn = "null",
doi = "https://doi.org/10.3745/TKIPS.2024.13.2.48",
author = "Jaehak Lee, Jongbeom Lim, Heonchang Yu",
keywords = "Cloud Computing, Network, Resource Management, Virtualization, Hypervisor, SR-IOV, Virtio",
abstract = "As functions that support virtualization on their own in hardware are developed, user applications having various workloads are
operating efficiently in the virtualization system. SR-IOV is a virtualization support function that takes direct access to PCI devices, thus 
giving a high I/O performance by minimizing the need for hypervisor or operating system interventions. With SR-IOV, network I/O
acceleration can be realized in virtualization systems that have relatively long I/O paths compared to bare-metal systems and frequent 
context switches between the user area and kernel area. To take performance advantages of SR-IOV, network resource management policies 
that can derive optimal network performance when SR-IOV is applied to an instance such as a virtual machine(VM) or container are 
being actively studied.This paper evaluates and analyzes the network performance of SR-IOV implementing I/O acceleration is compared 
with Virtio in terms of 1) network delay, 2) network throughput, 3) network fairness, 4) performance interference, and 5) multi-network. 
The contributions of this paper are as follows. First, the network I/O process of Virtio and SR-IOV was clearly explained in the virtualization 
system, and second, the evaluation results of the network performance of Virtio and SR-IOV were analyzed based on various performance 
metrics. Third, the system overhead and the possibility of optimization for the SR-IOV network in a virtualization system with high VM 
density were experimentally confirmed. The experimental results and analysis of the paper are expected to be referenced in the network 
resource management policy for virtualization systems that operate network-intensive services such as smart factories, connected cars, 
deep learning inference models, and crowdsourcing."
}