Protocol Efficiency and Resource Utilization in VPN Technologies: A Comparative Analysis of OpenVPN and WireGuard

Sura Ghanim Hussein; Syed Muhammad Fasih Ur Rehman

doi:10.51173/jt.v7i4.2768

Authors

Sura Ghanim Hussein Engineering Technical College – Baghdad, Middle Technical University, Baghdad, Iraq
Syed Muhammad Fasih Ur Rehman Faculty of Engineering, The Islamia University of Bahawalpur, Bahawalpur, Pakistan

DOI:

https://doi.org/10.51173/jt.v7i4.2768

Keywords:

VPN, OpenVPN, Wire Guard, Performance Evaluation, Latency

Abstract

Virtual Private Networks are essential for securing Internet communication, but the selection of a VPN protocol can substantially affect overall network performance. Nonetheless, typical VPN protocols (e.g., OpenVPN) are too secure relative to their worst-case latency and computational overhead. New-generation VPN protocols, such as WireGuard, are said to offer greater efficiency due to a lightweight cryptographic design. This paper then depicts a comparison trial of OpenVPN and WireGuard throughput under controlled cooperation. Download and upload speeds, latency, and CPU and RAM utilization were measured using the Speedtest application on a Windows 11 platform. The results reveal that WireGuard achieved network performance approaching the baseline, with 50.4 Mbps download speeds, low latency (8.01 ms), and low CPU consumption (3%). In contrast, OpenVPN decreased download speeds to 22.1 Mbps and was accompanied by high latency (160.38 ms). The results imply that WireGuard is a valid choice for latency-sensitive and throughput-demanding use cases. In contrast, OpenVPN is appropriate for use cases that focus on interoperability and established security.

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Author Biographies

Sura Ghanim Hussein, Engineering Technical College – Baghdad, Middle Technical University, Baghdad, Iraq

Department of Mechatronics Engineering Techniques

Syed Muhammad Fasih Ur Rehman, Faculty of Engineering, The Islamia University of Bahawalpur, Bahawalpur, Pakistan

Vibration Control, Control Engineering, Neural Networks

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