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diff --git a/content/conclusion.tex b/content/conclusion.tex index dcfd203..d964ae9 100644 --- a/content/conclusion.tex +++ b/content/conclusion.tex @@ -1,11 +1,45 @@ \chapter{Conclusion}\label{s:conclusion} -\todo{ - Briefly summarize your contributions, and share a glimpse of the implications of - this work for future research. -} +Datacenter manageability is a top-priority for the digital society. +Over 3 million jobs in the Netherlands directly depend on cloud services, which are hosted in datacenters~\cite{DBLP:journals/corr/IosupKLVG22}. +Datacenter digital twinning, a promising management technique can offer unique insight into complex facility behaviour. +In this thesis we pave the way to more advanced \gls{dcdt}s. +We contribute to the scientific community a set of findings that we hope will prove helpful in enabling predictive analytics in both existing \gls{dcdt}s and future projects. +Starting from a thorough investigation into the new, emerging field of datacenter digital twinning, we designed a system capable of incorporating sophisticated data analysis techniques. +We ended our project with a novel evaluation method used in a set of exhaustive experiments. +As such, we believe we answer the main research question by addressing each sub-research question. +\section{Answers to Research Questions} -\lipsum[1-2] +\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. + Our findings indicate that the field of datacenter digital twinning is still under development. + There exist few existing \gls{dcdt} deployments. + The current efforts in modelling datacenters focus on very specialized parts of the datacenter management, \ie cooling and heat modelling, network mapping. + These standalone systems fail to offer the holistic capabilities envisioned for \gls{dt}s. + The results of the literature survey are in \Cref{tab:dt_features_comparison}. + \Cref{tab:dt_features_comparison} contains systems which we found though a semi-structured literature review process. + We first used structured queries, followed by a mix of snowballing and manual search. + As a result, the second contribution to answering research question 2 is a holistic system model that encompasses the features of all the systems from \Cref{tab:dt_features_comparison} (see \Cref{fig:system_model}). + \item \emph{How to design a reference architecture for a predictive datacenter digital twin using discrete-event simulation?}\\ + To answer this research question, we first brainstormed the potential use-cases for a predictive \gls{dcdt}. + The use-cases are based on the findings of our literature survey. + We list the use-cases we found in \Cref{s:design}. + Based on a set of use-cases we created a set of functional and non-functional requirements to guide our system design. + Then, using the \emph{AtLarge Design Process} we created the reference architecture that enables predictive analysis for datacenter operators through digital twinning. + + \item \emph{How to validate and evaluate a datacenter digital twin architecture in relation to system requirements?}\\ + To answer the last research question we crated a prototype to evaluate our system. + Lacking the physical datacenter to experiment with, we came up with a novel digital twin evaluation method, that uses discrete-event simulation to model the physical datacenter. + Our main findings indicate that \gls{my_system} can reliably differentiate between large host failures and insignificant single host downtime using predictions based on the results from \code{OpenDC}, a state of the art datacenter modelling software. + Moreover, we show that \gls{my_system} can be used to incorporate a predictive analytics system and significantly lower the total number of task failures during a workload. +\end{enumerate} + +\section{Future Work} + +We envision \gls{dcdt}s as systems that encompass features necessary to model the entire datacenter behaviour. +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. +We predict that in the near future, a number of |