From 41332d82be61fad881ecef9e4317dffd5dc127bb Mon Sep 17 00:00:00 2001
From: mjkwiatkowski <mati.rewa@gmail.com>
Date: Mon, 6 Jul 2026 12:15:06 +0200
Subject: feat: finished section 6.1

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 \chapter{Conclusion}\label{s:conclusion}
 
 
-\todo{
-	Briefly summarize your contributions, and share a glimpse of the implications of
-	this work for future research.
-}
+Datacenter manageability is a top-priority for the digital society.
+Over 3 million jobs in the Netherlands directly depend on cloud services, which are hosted in datacenters~\cite{DBLP:journals/corr/IosupKLVG22}.
+Datacenter digital twinning, a promising management technique can offer unique insight into complex facility behaviour.
+In this thesis we pave the way to more advanced \gls{dcdt}s.
+We contribute to the scientific community a set of findings that we hope will prove helpful in enabling predictive analytics in both existing \gls{dcdt}s and future projects.
+Starting from a thorough investigation into the new, emerging field of datacenter digital twinning, we designed a system capable of incorporating sophisticated data analysis techniques.
+We ended our project with a novel evaluation method used in a set of exhaustive experiments.
+As such, we believe we answer the main research question by addressing each sub-research question.
 
+\section{Answers to Research Questions}
 
-\lipsum[1-2]
+\begin{enumerate}[label=\emph{RQ\textsubscript{\arabic*}}]
+	\item \emph{How to asses the current state-of-the-art of digital twinning for datacenters?}\\
+	      In order to answer this research question, we conducted a semi-structured literature review.
+	      Our findings indicate that the field of datacenter digital twinning is still under development.
+	      There exist few existing \gls{dcdt} deployments.
+	      The current efforts in modelling datacenters focus on very specialized parts of the datacenter management, \ie cooling and heat modelling, network mapping.
+	      These standalone systems fail to offer the holistic capabilities envisioned for \gls{dt}s.
+	      The results of the literature survey are in \Cref{tab:dt_features_comparison}.
+	      \Cref{tab:dt_features_comparison} contains systems which we found though a semi-structured literature review process.
+	      We first used structured queries, followed by a mix of snowballing and manual search.
+	      As a result, the second contribution to answering research question 2 is a holistic system model that encompasses the features of all the systems from \Cref{tab:dt_features_comparison} (see \Cref{fig:system_model}).
 
+	\item \emph{How to design a reference architecture for a predictive datacenter digital twin using discrete-event simulation?}\\
+	      To answer this research question, we first brainstormed the potential use-cases for a predictive \gls{dcdt}.
+	      The use-cases are based on the findings of our literature survey.
+	      We list the use-cases we found in \Cref{s:design}.
+	      Based on a set of use-cases we created a set of functional and non-functional requirements to guide our system design.
+	      Then, using the \emph{AtLarge Design Process} we created the reference architecture that enables predictive analysis for datacenter operators through digital twinning.
+
+	\item \emph{How to validate and evaluate a datacenter digital twin architecture in relation to system requirements?}\\
+	      To answer the last research question we crated a prototype to evaluate our system.
+	      Lacking the physical datacenter to experiment with, we came up with a novel digital twin evaluation method, that uses discrete-event simulation to model the physical datacenter.
+	      Our main findings indicate that \gls{my_system} can reliably differentiate between large host failures and insignificant single host downtime using predictions based on the results from \code{OpenDC}, a state of the art datacenter modelling software.
+	      Moreover, we show that \gls{my_system} can be used to incorporate a predictive analytics system and significantly lower the total number of task failures during a workload.
+\end{enumerate}
+
+\section{Future Work}
+
+We envision \gls{dcdt}s as systems that encompass features necessary to model the entire datacenter behaviour.
+It came to our attention, that with the explosive growth of \gls{ai} and the diversification of datacenters under way, \gls{dt}s will be indispensable in datacenter management.
+We predict that in the near future, a number of 
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