From 9681bc07728c028638b8b3764053589adeb3bbe6 Mon Sep 17 00:00:00 2001 From: mjkwiatkowski Date: Wed, 10 Jun 2026 10:12:28 +0200 Subject: feat: added a slide to argue against pure simulation for predictive analysis --- main.tex | 19 ++++++++++++++++++- 1 file changed, 18 insertions(+), 1 deletion(-) (limited to 'main.tex') diff --git a/main.tex b/main.tex index 4e034b5..c6011ce 100644 --- a/main.tex +++ b/main.tex @@ -115,7 +115,7 @@ \end{center} \tiny - \textbf{Figure E.3:} Due to insufficient technological foundations, + \textbf{Figure E.2:} Due to insufficient technological foundations, little work is available on DTs between 2003 and 2018, and it is only with the rapid growth of cloud computing, Internet-of-Things and Big Data analytics that DTs have reemerged~\cite{DBLP:conf/cirp/TAO2018169}. That is why nobody used digital twins to mirror datacenters earlier. @@ -130,7 +130,24 @@ US\$~\cite{DBLP:report/AnnualOutageAnalysis2025}. Only a constant bi-directional interaction (digital twin $\iff$ physical entity) can achieve this. \end{tcolorbox} + \begin{center} + \includegraphics[height=10em]{images/AthavaleBBMMPS24-3_cropped.pdf} + \end{center} + \tiny \textbf{Figure E.3:} Real-time control that is tightly-coupled with the IT equipment is a prerequisite for timely predictions within seconds/minutes~\cite{DBLP:journals/computer/AthavaleBBMMPS24}. \end{frame} +\begin{frame}\frametitle{Extra Slides: Alternatives to OpenDC} + \begin{tcolorbox}[title=Why not CFD/ML/Graphs?] + \begin{enumerate} + \item Computational Fluid Dynamics (CFD) have high computation overhead, unsuitable for real-time simulation of a dynamic datacenter. + Moreover oftentimes a poorly configured CFD model can lead to high error rates~\cite{DBLP:conf/sensys/WangZD0TCWZ20}. + + \item Data-driven Machine Learning performs poorly by the cases not covered in the training data. + + + \end{enumerate} + \end{tcolorbox} +\end{frame} + \end{document} -- cgit v1.2.3