From d06a150557cdb07e5c2efecd3c9f7e79ae5dd003 Mon Sep 17 00:00:00 2001
From: mjkwiatkowski <mati.rewa@gmail.com>
Date: Wed, 8 Jul 2026 18:28:49 +0200
Subject: feat: added the overview boxes to background and design

---
 content/design.tex | 50 ++++++++++++++++++++++++++++++++++++++++++++------
 1 file changed, 44 insertions(+), 6 deletions(-)

(limited to 'content/design.tex')

diff --git a/content/design.tex b/content/design.tex
index d4473b0..a41d84d 100644
--- a/content/design.tex
+++ b/content/design.tex
@@ -14,27 +14,65 @@ We present here the stakeholders identified by our literature survey (see \Cref{
 Afterwards, we list the functional and non-functional requirements for \mysystem.
 
 \subsection{Stakeholders}\label{sss:stakeholders}
-\begin{enumerate}[label=\textbf{S\arabic*:},align=left]
-	\item \textbf{Datacenter} \\
+We identify four main stakeholders of a predictive datacenter digital twin:
+\begin{enumerate}[label=\textbf{S\arabic* --},align=left]
+	\item \textbf{Datacenter Managers}\\
+	      Responsible for maintenance and operation of the warehouse, operators manage the datacenter daily.
+	      They interact with the servers, bring downed hosts up and ensure customers' services run smoothly at all times.
+	      Datacenter operators need to ensure different \gls{sla}s are met, energy costs are balanced and carbon emission quota is maintained.
+	\item \textbf{Datacenter Technicians}\\
+	      The term datacenter engineers encompasses datacenter architects and technicians alike.
+	      From the moment the datacenter layout is determined, to the physical process of booting the server racks for the first time, datacenter engineers help build and maintain the datacenter.
+	      They must continuously adapt to changing requirements and ensure everything goes smoothly~\cite{DBLP:journals/computer/AthavaleBBMMPS24}.
+	\item \textbf{Scientists and Academia}\\
+	      Digital twinning generates unprecedented amount of data.
+	      To bring valuable insights, the ingested metrics must be effectively analyzed.
+	      Scientists can draw conclusions from the monitoring data and in some deployments already benefit from the voluminous output of \gls{dcdt}s~\cite{DBLP:conf/noms/ZhangZLZWC22}.
+	\item \textbf{Customers and Users}\\
+	      Digital twins are already used to visualize both facilities and human beings alike for the benefit of users and customers.
+	      Cloud and HPC users are not directly interacting with the system, but pay for services hosted in the datacenter and are one of the primary stakeholders of digital twinning.
+	      Not only through 3D datacenter visualizations, but also from the continuously generated metrics can users and customers benefit from \gls{dcdt}s.
 \end{enumerate}
 
 \subsection{Use-cases}\label{sss:use_cases}
-\begin{enumerate}[label=\textbf{UC\arabic*:},align=left]
-	\item \textbf{Datacenter} \\
+Based on the identified stakeholders we list 6 potential use-cases for a predictive datacenter digital twin:
+\begin{enumerate}[label=\textbf{UC\arabic* --},align=left]
+	\item \textbf{Energy Optimization} \\
+	      Predicting and modeling energy optimization is curcial for \gls{dcdt}s.
+	      It is the main use-case of some existing systems~\cite{DBLP:conf/sc/BrewerMKWBHSGGW24}.
+	      Effective energy optimization, including the adjustments to the consumed energy type is a crucial use-case of \gls{dcdt}s.
+	\item \textbf{Failure Management} \\
+	      Predictive maintenance of both hardware and software failures alike, by simulating the possible failure distribution of a running workload, can lower downtime, terminated tasks and ensure \gls{sla}s are not missed~\cite{DBLP:journals/computer/AthavaleBBMMPS24}.
+	\item \textbf{Heat Modelling} \\
+	      Heat modeling is the primary use case of existing \gls{dcdt}s (see \Cref{tab:dt_features_comparison}).
+	      Correct thermal management of the warehouse can optimize cooling strategies, leading to lower bills and maintenance costs.
+	\item \textbf{Network Traffic Modelling} \\
+	      Congestion management and traffic routing can effectively benefit from digital twinning.
+	      Detecting bottlenecks, adjusting datacenter protocols and calibrating switches and interconnects is already a important use-case for \gls{dcdt}~\cite{DBLP:conf/sigcomm/HongWDSSHZY21}.
+	\item \textbf{Virtual Prototyping} \\
+
+	\item \textbf{Monitoring and Visualization} \\
 \end{enumerate}
 
 \subsection{Functional Requirements}\label{sss:functional_requirements}
-\begin{enumerate}[label=\textbf{FR\arabic*:},align=left]
+\begin{enumerate}[label=\textbf{FR\arabic* --},align=left]
 	\item \textbf{Datacenter} \\
 \end{enumerate}
 
 \subsection{Non-functional Requirements}\label{sss:non_functional_requirements}
-\begin{enumerate}[label=\textbf{NFR\arabic*:},align=left]
+\begin{enumerate}[label=\textbf{NFR\arabic* --},align=left]
 	\item \textbf{Datacenter} \\
 \end{enumerate}
 
 \section{Design of \emph{Sunfish}}\label{ss:design_of_mysystem}
 
+\begin{figure}[t]
+	\includegraphics[width=\linewidth]{images/ref_architecture.pdf}
+	\caption{ The predictive datacenter digital twin reference architecture.
+		We call the system \emph{Sunfish}.
+		The architecture was designed with the \emph{AtLarge Design Process}~\cite{DBLP:conf/icdcs/IosupVTETBFMT19} over several iterations in the past months}
+\end{figure}
+
 \subsection{Digital Thread}
 
 \subsection{Data Storage}
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