\chapter{Introduction} % Main chapter title

\label{Introduction}

Peer-to-peer overlay VPNs promise to restore genuine decentralization
by enabling direct connectivity between nodes regardless of NAT or
firewall restrictions. Yet practitioners choosing among the growing
number of mesh VPN implementations must rely largely on anecdotal
evidence: systematic, reproducible comparisons under realistic
conditions are scarce.

This thesis addresses that gap. We benchmark ten peer-to-peer VPN
implementations across seven workloads and four network impairment
profiles, yielding over 300 unique measurements. We complement these
performance benchmarks with a source code analysis of each
implementation, verified through direct engagement with the respective
maintainers. The entire experimental framework is built on Nix, NixOS,
and the Clan deployment system, making every result independently
reproducible.

\section{Motivation}

Peer-to-peer architectures promise censorship-resistant, fault-tolerant
infrastructure by eliminating single points of failure
\cite{shukla_towards_2021}.
These architectures underpin a growing range of systems---from IoT
edge computing
and content delivery networks to blockchain platforms like Ethereum.
Yet realizing these benefits requires distributing nodes across
genuinely diverse hosting entities.

In practice, this diversity remains illusory.
Amazon, Hetzner, and OVH collectively host 70\% of all Ethereum nodes
(see Figure~\ref{fig:ethernodes_hosting}),
concentrating nominally decentralized infrastructure
within a handful of cloud providers.
More concerning, these providers operate under overlapping regulatory
jurisdictions,
predominantly the United States and the European Union.
This concentration undermines technical sovereignty:
a single governmental action could compel service termination,
data disclosure, or traffic manipulation across a majority of the network.

\begin{figure}[H]
  \centering
  \includegraphics[width=1\textwidth]{Figures/ethernodes_hosting.png}
  \caption{Distribution of Ethereum nodes hosted by various providers
  \cite{noauthor_isps_nodate}}
  \label{fig:ethernodes_hosting}
\end{figure}

Why does this centralization persist despite the explicit goals of
decentralization?
The answer lies in the practical barriers to self-hosting.
Cloud providers offer static IP addresses and publicly routable endpoints,
eliminating the networking complexity that plagues residential and
small-office deployments.
Most internet-connected devices sit behind Network Address Translation (NAT),
which prevents incoming connections without explicit port forwarding
or relay infrastructure.
Combined with dynamic IP assignments from ISPs, maintaining stable
peer connectivity
from self-hosted infrastructure traditionally required significant
technical expertise.

Overlay VPNs offer a solution to this fundamental barrier.
By establishing encrypted tunnels that traverse NAT boundaries,
mesh VPNs enable direct peer-to-peer connectivity without requiring
static IP addresses or manual firewall configuration.
Each node receives a stable virtual address within the overlay network,
regardless of its underlying network topology.
This capability is transformative:
it allows a device behind consumer-grade NAT to participate
as a first-class peer in a distributed system,
removing the primary technical advantage that cloud providers hold.

The Clan deployment framework builds on this foundation.
Clan leverages Nix and NixOS to eliminate entire classes of
configuration errors prevalent in contemporary infrastructure deployment,
reducing operational overhead to a degree where a single administrator
can reliably self-host complex distributed services.
Overlay VPNs are central to Clan's architecture,
providing the secure peer connectivity that enables nodes
to form cohesive networks regardless of their physical location or
NAT situation.
As illustrated in Figure~\ref{fig:vision-stages}, Clan envisions
a web interface that enables users to design and deploy private P2P networks
with minimal configuration, assisted by an integrated LLM
for contextual guidance and troubleshooting.

During the development of Clan, a recurring challenge became apparent:
practitioners held divergent preferences for mesh VPN solutions,
each citing different edge cases where their chosen VPN
proved unreliable or lacked essential features.
These discussions were largely grounded in anecdotal evidence
rather than systematic evaluation.
This observation revealed a clear need for rigorous,
evidence-based comparison of peer-to-peer overlay VPN implementations.

\subsection{Related Work}

Existing research offers only partial coverage of this space.
Lackorzynski et al.\ \cite{lackorzynski_comparative_2019} benchmark
OpenVPN, IPSec, Tinc, Freelan, MACsec, and WireGuard in the context
of industrial communication systems, measuring point-to-point
throughput, latency, and CPU overhead. Their work does not address
overlay network behavior such as NAT traversal or dynamic peer discovery.
The most closely related study by Kjorveziroski et al.\
\cite{kjorveziroski_full-mesh_2024} evaluates full-mesh VPN solutions
for distributed systems, analyzing throughput, reliability under packet
loss, and relay behavior for VPNs including ZeroTier. However, it
focuses primarily on solutions with a central point of failure and
limits its workloads to synthetic iperf3 tests. This thesis extends
that foundation by evaluating a broader set of VPN implementations
with emphasis on fully decentralized architectures, exercising them
under real-world workloads such as video streaming and package
downloads, applying multiple network impairment profiles, and
providing a fully reproducible experimental framework built on
Nix, NixOS, and Clan.

Beyond filling this research gap, a further goal was to create a fully
automated benchmarking framework capable of generating a public
leaderboard, similar in spirit to the js-framework-benchmark
(see Figure~\ref{fig:js-framework-benchmark}). By providing an
accessible web interface with regularly updated results, we hope to
encourage P2P VPN developers to optimize their implementations in
pursuit of top rankings.

\section{Research Contribution}

This thesis makes the following contributions:

\begin{enumerate}
  \item A comprehensive benchmark of ten peer-to-peer VPN
    implementations across seven workloads. Including real-world
    video streaming and package downloads; and four network
    impairment profiles, producing over 300 unique measurements.
  \item A source code analysis of all ten VPN implementations,
    combining manual code review with LLM-assisted analysis,
    followed by verification through direct engagement with the
    respective maintainers on GitHub.
  \item A fully reproducible experimental framework built on
    Nix, NixOS, and the Clan deployment system, with pinned
    dependencies, declarative system configuration, and
    deterministic cryptographic material generation, enabling
    independent replication of all results.
  \item A performance analysis demonstrating that Tailscale
    outperforms the Linux kernel's default networking stack under
    degraded conditions, and that kernel parameter tuning; Reno
    congestion control in place of CUBIC, with RACK
    disabled; yields measurable throughput improvements.
  \item The discovery of several security vulnerabilities across
    the evaluated VPN implementations.
  \item An automated benchmarking framework designed for public
    leaderboard generation, intended to encourage ongoing
    optimization by VPN developers.
\end{enumerate}

\begin{figure}[H]
  \centering
  \includegraphics[width=1\textwidth]{Figures/krause-js-framework.png}
  \caption{js-framework-benchmark results for Chrome 144.0
  \cite{krause_krausestjs-framework-benchmark_2026}}
  \label{fig:js-framework-benchmark}
\end{figure}

\begin{figure}[h]
  \centering

  % Row 1
  \begin{subfigure}{0.45\textwidth}
    \centering
    \includegraphics[width=\linewidth]{Figures/vision/stage1.png}
    \caption{Stage 1}
  \end{subfigure}
  \hfill
  \begin{subfigure}{0.45\textwidth}
    \centering
    \includegraphics[width=\linewidth]{Figures/vision/stage2.png}
    \caption{Stage 2}
  \end{subfigure}

  \vspace{1em} % Add spacing between rows

  % Row 2
  \begin{subfigure}{0.45\textwidth}
    \centering
    \includegraphics[width=\linewidth]{Figures/vision/stage3.png}
    \caption{Stage 3}
  \end{subfigure}
  \hfill
  \begin{subfigure}{0.45\textwidth}
    \centering
    \includegraphics[width=\linewidth]{Figures/vision/stage4.png}
    \caption{Stage 4}
  \end{subfigure}

  \vspace{1em} % Add spacing between rows

  % Row 3
  \begin{subfigure}{0.45\textwidth}
    \centering
    \includegraphics[width=\linewidth]{Figures/vision/stage5.png}
    \caption{Stage 5}
  \end{subfigure}
  \hfill
  \begin{subfigure}{0.45\textwidth}
    \centering
    \includegraphics[width=\linewidth]{Figures/vision/stage6.png}
    \caption{Stage 6}
  \end{subfigure}

  \vspace{1em} % Add spacing between rows

  % Row 4
  \begin{subfigure}{0.45\textwidth}
    \centering
    \includegraphics[width=\linewidth]{Figures/vision/stage7.png}
    \caption{Stage 7}
  \end{subfigure}
  \hfill
  \begin{subfigure}{0.45\textwidth}
    \centering
    \includegraphics[width=\linewidth]{Figures/vision/stage8.png}
    \caption{Stage 8}
  \end{subfigure}

  \caption{Visionary Webinterface to Setup a Clan Family Network}
  \label{fig:vision-stages}
\end{figure}

