feat: fixing the table in the background

6 files changed, 82 insertions, 25 deletions

diff --git a/citations2/iteration1/acm/3563357.3564050.pdf b/citations/CaoBUILDSYS2022.pdf
index bdbcd8c..bdbcd8c 100644
--- a/citations2/iteration1/acm/3563357.3564050.pdf
+++ b/citations/CaoBUILDSYS2022.pdf
diff --git a/citations2/iteration1/acm/3472727.3472802.pdf b/citations/HongNAI2021.pdf
index f9b1e1d..f9b1e1d 100644
--- a/citations2/iteration1/acm/3472727.3472802.pdf
+++ b/citations/HongNAI2021.pdf
diff --git a/citations2/iteration1/acm/3408308.3427982.pdf b/citations/WangBUILDSYS2020.pdf
index 5bf156c..5bf156c 100644
--- a/citations2/iteration1/acm/3408308.3427982.pdf
+++ b/citations/WangBUILDSYS2020.pdf
diff --git a/content/background.tex b/content/background.tex
index 4218380..4d84a78 100644
--- a/content/background.tex
+++ b/content/background.tex
@@ -1,8 +1,10 @@
 \chapter{Background}\label{s:background}
 
+\section{Overview}\label{s:background_overview}
 
 \section{Digital Twinning}\label{ss:digital-twinning}
 
+
 % To fix: remove the \gls commands for ExaDigiT.
 % This is getting silly.
 \subsection{What is Digital Twinning?}\label{sss:what_is_digital_twinning}
@@ -72,7 +74,7 @@ The process of inference from data to provide the best explanation is called abd
 
 
 \section{Datacenters}\label{ss:datacenters}
-\subsection{Datacenter simulation}\label{sss:simulation}
+\subsection{A Primer on Datacenter simulation}\label{sss:simulation}
 \input{sources/dt_features_comparison.tex}
 
 Explain the high risk phenomena that occur in datacenters, which includes failures.
diff --git a/main.bib b/main.bib
index 285859d..ba68dd4 100644
--- a/main.bib
+++ b/main.bib
@@ -573,3 +573,58 @@
         biburl = {https://dblp.org/rec/conf/sensys/LiW0Z0T23.bib},
         bibsource = {dblp computer science bibliography, https://dblp.org},
 }
+
+@inproceedings{DBLP:conf/sensys/CaoW0022,
+        author = {Zhiwei Cao and Ruihang Wang and Xin Zhou and Yonggang Wen},
+        editor = {Jorge Ortiz},
+        title = {Reducio: model reduction for data center predictive digital
+                 twins via physics-guided machine learning},
+        booktitle = {Proceedings of the 9th {ACM} International Conference on
+                     Systems for Energy-Efficient Buildings, Cities, and
+                     Transportation, BuildSys 2022, Boston, Massachusetts,
+                     November 9-10, 2022},
+        pages = {1--10},
+        publisher = {{ACM}},
+        year = {2022},
+        url = {https://doi.org/10.1145/3563357.3564050},
+        doi = {10.1145/3563357.3564050},
+        timestamp = {Wed, 04 Dec 2024 09:43:28 +0100},
+        biburl = {https://dblp.org/rec/conf/sensys/CaoW0022.bib},
+        bibsource = {dblp computer science bibliography, https://dblp.org},
+}
+
+@inproceedings{DBLP:conf/sigcomm/HongWDSSHZY21,
+        author = {Hanshu Hong and Qin Wu and Feng Dong and Wei Song and Ronghua
+                  Sun and Tao Han and Cheng Zhou and Hongwei Yang},
+        title = {NetGraph: An Intelligent Operated Digital Twin Platform for
+                 Data Center Networks},
+        booktitle = {NAI'21: Proceedings of the {ACM} {SIGCOMM} 2021 Workshop on
+                     Network-Application Integration, Virtual Event, USA, August
+                     27, 2021},
+        pages = {26--32},
+        publisher = {{ACM}},
+        year = {2021},
+        url = {https://doi.org/10.1145/3472727.3472802},
+        doi = {10.1145/3472727.3472802},
+        timestamp = {Sun, 19 Jan 2025 13:17:55 +0100},
+        biburl = {https://dblp.org/rec/conf/sigcomm/HongWDSSHZY21.bib},
+        bibsource = {dblp computer science bibliography, https://dblp.org},
+}
+
+@inproceedings{DBLP:conf/sensys/WangZD0TCWZ20,
+        author = {Ruihang Wang and Xin Zhou and Linsen Dong and Yonggang Wen and
+                  Rui Tan and Li Chen and Guan Wang and Feng Zeng},
+        title = {Kalibre: Knowledge-based Neural Surrogate Model Calibration for
+                 Data Center Digital Twins},
+        booktitle = {BuildSys '20: The 7th {ACM} International Conference on
+                     Systems for Energy-Efficient Buildings, Cities, and
+                     Transportation, Virtual Event, Japan, November 18-20, 2020},
+        pages = {200--209},
+        publisher = {{ACM}},
+        year = {2020},
+        url = {https://doi.org/10.1145/3408308.3427982},
+        doi = {10.1145/3408308.3427982},
+        timestamp = {Wed, 04 Dec 2024 09:45:46 +0100},
+        biburl = {https://dblp.org/rec/conf/sensys/WangZD0TCWZ20.bib},
+        bibsource = {dblp computer science bibliography, https://dblp.org},
+}
diff --git a/sources/dt_features_comparison.tex b/sources/dt_features_comparison.tex
index 2bc3305..cdad073 100644
--- a/sources/dt_features_comparison.tex
+++ b/sources/dt_features_comparison.tex
@@ -1,27 +1,27 @@
-\begin{table}[t]
+\begin{table}[h]
 	\centering
 	\renewcommand{\arraystretch}{1.4}
-	\begin{tabular}{m{0.4\linewidth}ccccc}
-		\toprule
-                Feature                                     & ExaDigiT~\cite{DBLP:conf/sc/BrewerMKWBHSGGW24} & SmartDC~\cite{DBLP:conf/noms/ZhangZLZWC22} & DyTwin~\cite{DBLP:conf/sc/TaheriBPRHDEWPM24} & ChatTwin~\cite{DBLP:conf/sensys/LiW0Z0T23}\\
-		\midrule                                                                                                                                                                                  
-		Virtual Prototyping                         &                                                & \ding{51}                                  &                                              &\\
-		Scenario Exploration                        &                                                &                                            &                                              &\\
-		3D Facility Modelling                       & \ding{51}                                      & \ding{51}                                  &                                              &\\
-		Predictive maintenance                      &                                                &                                            &                                              &\\
-		Predictive energy modelling                 &                                                & \ding{51}                                  &                                              &\\
-		Reliability and availability modeling       &                                                &                                            &                                              &\\
-		Cooling system modelling                    &                                                & \ding{51}                                  &                                              &\\
-		Network modelling                           &                                                &                                            &                                              &\\
-		Predictive modelling                        &                                                &                                            &                                              &\\
-		Power/Energy consumption optimization (PUE) &                                                & \ding{51}                                  &                                              &\\
-		Heat and Airflow distribution modelling     &                                                & \ding{51}                                  &                                              &\\
-		Visual analytics dashboard                  &                                                &                                            &                                              &\\
-		Forensic analysis and diagnostics           &                                                &                                            &                                              &\\
-		Failure detection                           &                                                &                                            &                                              &\\
-		Operational optimization                    &                                                &                                            &                                              &\\
-		Resource allocation                         &                                                &                                            &                                              &\\
-		\midrule
-	\end{tabular}
-	\caption{Comparison of selected features of existing datacenter digital twins.}
+	\resizebox{\columnwidth}{!}{
+		\begin{tabular}{lm{0.2\linewidth}m{0.25\linewidth}m{0.3\linewidth}l}
+			\toprule
+			Project                                         & Simulation\qquad Technique      & Focus                               & Stakeholders & Highlighted Features \\
+			\midrule
+			ExaDigiT~\cite{DBLP:conf/sc/BrewerMKWBHSGGW24}  & CFD/HT                          & Energy Loss\newline Prediction      &              &                      \\
+			\midrule
+			SmartDC~\cite{DBLP:conf/noms/ZhangZLZWC22}      & CFD/HT, BIM, AI                 & Heat Modelling                      &              &                      \\
+			\midrule
+			DyTwin~\cite{DBLP:conf/sc/TaheriBPRHDEWPM24}    & Gaussian Process Regression, ML & Anomaly Detection                   &              &                      \\
+			\midrule
+			ChatTwin~\cite{DBLP:conf/sensys/LiW0Z0T23}      & \textbf{\large?}                & Configuration\newline Automation    &              &                      \\
+			\midrule
+			Reducio~\cite{DBLP:conf/sensys/CaoW0022}        & POD                             & Heat and Airflow\newline Prediction &              &                      \\
+			\midrule
+			NetGraph~\cite{DBLP:conf/sigcomm/HongWDSSHZY21} & Graphs                          & Network Management                  &              &                      \\
+			\midrule
+			Kalibre~\cite{DBLP:conf/sensys/WangZD0TCWZ20}   & ML, CFD                         & Heat Modelling                      &              &                      \\
+			\bottomrule
+		\end{tabular}
+	}
+	\caption{Comparison of selected datacenter digital twins. \textbf{Features:} 3D = 3D Visualizations; CH = Cooling/Heat, PE = Power/Energy Consumption, F = Failures, N = Network, FS = FaaS, SE = Scenario Exploration, VP = Virtual Prorotyping, FD = Federation; \textbf{Tools:} AI = Artificial Intelligence, ML = Machine Learning, ODA = Operational Data Analysis; $\dagger$ Predictive Analysis; $\star$ = Descriptive Analysis, $\ddagger$ = Prescriptive Analysis.}
 \end{table}
+