feat: changed the TOC and added the preamble

1 files changed, 7 insertions, 4 deletions

diff --git a/content/conclusion.tex b/content/conclusion.tex
index 122b2be..83a499c 100644
--- a/content/conclusion.tex
+++ b/content/conclusion.tex
@@ -9,11 +9,11 @@ Starting from a thorough investigation into the new, emerging field of datacente
 We ended our project with a novel evaluation method used in a set of exhaustive experiments.
 We answer the main research question by addressing each sub-research question.
 
-\section{Answers to Research Questions}\label{ss:answers_to_rqs}
+\section{Answers to Each Research Question}\label{ss:answers_to_rqs}
 
 \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.
+	      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, and there exist few \gls{dcdt} deployments.
 	      The current efforts in modelling datacenters focus on very specialized parts of datacenter management, \ie cooling and heat modelling, network mapping.
 	      Many crucial features, inherent to the \gls{dt} definition are still missing from current \gls{dcdt}s.
@@ -38,10 +38,13 @@ We answer the main research question by addressing each sub-research question.
 
 \section{Future Work}\label{ss:future_work}
 
+\subsection{A Strong, New Principle of \gls{dcdt} Design}\label{sss:future_work_in_analytics}
 We envision \gls{dcdt}s as systems that encompass features necessary to model the entire datacenter.
-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.
-To power the predictions we envision an \gls{ml}-based inference engine as a necessary component of digital twinning.
+It came to our attention that with the growth of \gls{ai} and the diversification of datacenters under way, \gls{dt}s will be indispensable in datacenter management.
+To power the predictions, we envision an \gls{ml}-based inference engine as a necessary component of digital twinning.
 The need for \gls{ml} arises naturally in scenarios where large volumes of data, requiring little to no preprocessing meet the demand for estimating future facility behaviour.
+
+\subsection{}\label{sss:future_work_in_failures}
 For future work in failure prediction, we envision an \gls{abc} approach to estimate the real failure distribution within the datacenter.
 Additionally, power usage optimization is a critical concern in datacenter management.
 We hope future attempts to enhance datacenter digital twinning can enable datacenter operators with actionable insights towards lowering the power consumption.