From a4102d0252236e85b2813160b4b11e3a19a00d62 Mon Sep 17 00:00:00 2001
From: mjkwiatkowski <mati.rewa@gmail.com>
Date: Fri, 13 Feb 2026 12:46:54 +0100
Subject: feat: added some refinements to the introduction

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 \chapter{Introduction}\label{s:intro}
+Today's transportation systems, education and government largely depend on server-side services, which are hosted in datacentres~\cite{DBLP:journals/corr/IosupKLVG22}.
+To facilitate the rising demand managers expand datacenters with new components and more heterogenous architectures (e.g., GPUs and NPUs)~\cite{DBLP:conf/date/MilojicicFDR21}.
+However, in return datacenter complexity increases significantly.
+To make better operational decisions despite the massive scale, new, promising technologies arise, such as datacenter Digital Twins.
 
-\todo{
-This section includes some motivations behind the work, explicitly or implicitly
-highlights the research question, provides a high-level explanation of the
-solution, and describes the contributions.
-}
+\section{Context}\label{s:context}
+Datacenters are one of the most important components of the digital society. 
+For example, over 25\% of professionals in the Netherlands depend on cloud services in their everyday work. 
+Faced with growing demand, this fraction will exceed 35\% by 2025~\cite{DBLP:journals/corr/IosupKLVG22}. 
+What is more, the surge of AI and Machine Learning workloads opens the need for versatile server architectures, pushing datacenter managers to meet customer expectations by adding more specialized hardware~\cite{DBLP:conf/date/MilojicicFDR21}. 
+In return, operating a modern datacenter with thousands of diversified servers presents a yet unsolved, non-trivial challenge that requires fast and well-informed decisions from on-site engineers.
 
+To aid in datacenter management, operators turn to \gls{oda}, which is the process of analyzing monitoring data to gain insights into the system behavior. 
+For example, OMNI at \gls{nersc} and Wintermute at \gls{lrz} employ descriptive analytics to optimize power usage effectivenes~\cite{DBLP:conf/icppw/BourassaJBCJVS19} and prescriptive analysis for energy efficient scheduling~\cite{DBLP:conf/hpdc/NettiMGOTO020}. 
+Nonetheless, we observe a critical lack of predictive analysis capabilities~\cite{DBLP:conf/wosp/SumanCNTMI24} among the existing \gls{oda} frameworks. 
+In result, datacenter operators are often confronted with operational decisions with limited time to react, which can lead to missed \gls{sla}.  
 
-\lipsum[1-2]
+``Lab-built, preproduction, or early hardware does \textit{not} work as defined, does \textit{not} work reliably and does \textit{not} stay the same from day to day'',
+according to Frederick P. Brooks. 
+A solution is a dependable simulator of the system~\cite{DBLP:books/daglib/Brooks0080747}.
+A novel improvement on simulation is a datacenter \gls{dt}~\cite{DBLP:journals/computer/AthavaleBBMMPS24}.
 
 
+\section{Problem statement}\label{s:problem-statement}
+
+\section{Research Questions}\label{s:research-questions}
+
+
+
+\section{Research Methodology}\label{s:research-methodology}
+
+\section{Thesis Contributions}\label{s:thesis-contributions}
+
+\section{Plagiarism Declaration}\label{s:plagiarism-declaraion}
+I hereby declare that this thesis is my own independent work and writing. 
+The thesis does not contain any material copied from other sources (person, Internet, or AI), and has not been submitted for assessment elsewhere.
+
+\section{Societal Impact}\label{s:societal-impact}
+
+\section{Thesis Structure}\label{s:thesis-structure}
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