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diff --git a/content/background.tex b/content/background.tex index 5ab53dc..8349bcf 100644 --- a/content/background.tex +++ b/content/background.tex @@ -4,33 +4,66 @@ The contribution in this chapter is three-fold: \begin{enumerate}[label=\emph{C\textsubscript{\arabic*}}, itemsep=0.2pt] - \item We provide a brief overview on datacenter simulation (\Cref{sss:simulation}), compute failures (\Cref{sss:failures}), and digital twinning (\Cref{sss:what_is_digital_twinning}). - \item We survey the state-of-the-art concerning datacenter digital twinning (\Cref{ss:digital_twins_for_datacenters}). + \item We provide a brief overview on datacenters (\Cref{ss:datacenters}) datacenter simulation (\Cref{sss:simulation}), compute failures (\Cref{sss:failures}), and digital twinning (\Cref{ss:digital-twinning}). + \item We survey the state-of-the-art concerning datacenter digital twinning (\Cref{sss:advanced_dts}). \item We construct a system model for existing datacenter digital twins (\Cref{ss:system_model_for_dcdts}) \end{enumerate} \end{mynote} \section{Datacenters}\label{ss:datacenters} -In this section we provide a short background on datacenter simulation and compute failures. -We find it useful to provide a brief introduction to both topics so as to ensure reader's fullest understanding of subsequent chapters. -Since datacenters are important building blocks of the digital society, reliable warehouse management is a key priority for datacenter operators. -Incorrect management decisions can lead to missed \gls{sla}s~\cite{DBLP:journals/corr/IosupKLVG22} and even large financial penalties~\cite{DBLP:report/AnnualOutageAnalysis2025}. -However, efficient and timely management is a difficult challenge, because datacenters are extremely complex facilities. -To help datacenter operators, the scientific community proposes to simulate datacenters to make more informed decisions. +In this section we provide a short background on datacenters, datacenter simulation and compute failures. +We find it useful to provide a brief introduction to these topics so as to ensure reader's fullest understanding of subsequent chapters. +%What are the parts of a data center? + +A datacenter is ``a physical room, building, or facility for the purpose of the storage, management, and dissemination of data and information, including training artificial intelligence, housing IT infrastructure, computer systems, and associated components.''~\cite{Wikipedia:article/Datacenter}. +In essence, datacenters contain a large amount servers, and everything that is needed to maintain them. +Most often servers are specially-designed motherboards with a (multicore) \gls{cpu}, \gls{ram} and storage. +More diverse servers include a \gls{cpu}, \gls{tpu}, or \gls{npu}. +To efficiently organize the datacenter, servers are placed within server \emph{racks}. +To maintain a large number of server racks, datacenters contain a cooling system to control the heat transfer and temperature of both the hardware and the entire facility. +Additionally, datacenters consume vast amounts of electricity~\cite{Wikipedia:article/Datacenter}. +Because of this, the datacenter power supply play a critical role in keeping the services running on the servers always available. +An example datacenter in \gls{cern}, is depicted on \Cref{fig:datacenter}. + +\begin{figure}[t] + \centering + \includegraphics[width=0.9\linewidth]{images/datacenter.jpg} + \caption[Datacenter in CERN.]{Example of a datacenter in \gls{cern}, Switzerland (2010)~\cite{Wikipedia:article/Datacenter}. In the figure we can see servers within servers racks, and the network cables.} + \label{fig:datacenter} +\end{figure} + +%Who are the stakeholders? +Datacenters form the backbone of the digital society. +The main stakeholders, besides the companies in the \gls{it} sector, are intelligent healthcare, remote work, online gaming, digital government and education, banking and finance, transport and logistics~\cite{DBLP:journals/corr/IosupKLVG22}. +All of the above industries need reliable datacenters to work well in the 21\textsuperscript{st} century. + +%Where does the actual complexity come from? +The high demand for online services drives datacenter complexity. +Moreover, due to the Jevon's paradox of Computer Systems~\cite{Wikipedia:article/JevonsParadox}, improved availability increases the demand. +As a result, datacenters contain hundreds, or even thousands of hardware components. +Every device may have a different vendor, new configuration, unusual interface \etc +Because of this, datacenter operators are often faced with difficult operational and architectural challenges~\cite{Wiley:book/Condor2005,DBLP:conf/ccgrid/MastenbroekAJLB21}, which span software and performance engineering. +Making sure that all the parts of the datacenter work together is a tough task. +What drives datacenter complexity even further is that sophisticated systems are not merely a sum of their parts~\cite{Wikipedia:article/Systems_Thinking}. +The combination of the above factors makes datacenter management a difficult, non-trivial challenge. \subsection{Datacenter Simulation}\label{sss:simulation} \input{sources/simulator_comparison.tex} + +Efficient and timely datacenter management is a difficult challenge, because datacenters are extremely complex facilities. +They require deep understanding to operate properly. +However, running real-world experiments is costly in both time and resources. +Additionally, experimentation \emph{in situ} is unsustainable and difficult to reproduce. +Alternatives to real-world experiments include simulation and mathematical analysis. +Because mathematical analysis is not scalable to modern datacenters~\cite{DBLP:conf/ccgrid/MastenbroekAJLB21}, in this project we only consider simulation as a foundation for the \gls{dcdt}. +%To help datacenter operators, the scientific community proposes to simulate datacenters to make more informed decisions. + Simulation empowers better design, testing and management of datacenters~\cite{DBLP:conf/ccgrid/MastenbroekAJLB21}. A well-designed datacenter simulator can estimate a months-long workload in a few minutes or hours. To simulate is to ``imitate of real-world process or system over time, enabling the study of, and experimentation with the internal interactions of complex systems''~\cite{DBLP:books/daglib/0034857} In this project we only consider \emph{discrete-event simulation}. - Discrete-event simulation represents system operations as a sequence of events over time, with an assumption that no changes occur between the events. Due to the scale and complexity of datacenters, most simulators use discrete-event simulation~\cite{DBLP:conf/ccgrid/MastenbroekAJLB21}. - -Alternatives to simulation include real-world experimentation and mathematical analysis. -However, experimentation \emph{in situ} is unsustainable, expensive and difficult to reproduce and mathematical analysis is not scalable to modern datacenters~\cite{DBLP:conf/ccgrid/MastenbroekAJLB21}. -Therefore, in this project we only consider simulation as a foundation for the \gls{dcdt}. There exist many datacenter simulation tools, for example DGSim~\cite{DBLP:conf/europar/IosupSE08}, CloudSim~\cite{DBLP:journals/spe/CalheirosRBRB11}, SimGrid~\cite{DBLP:journals/corr/CasanovaGLQS13}, iCanCloud~\cite{DBLP:journals/grid/NunezVCCCL12}, GroudSim~\cite{DBLP:conf/europar/OstermannPPF10} and OpenDC~\cite{DBLP:conf/ccgrid/MastenbroekAJLB21}. See \Cref{tab:datacenter_simulator_comparison} for a comparison of selected datacenter simulators, combined by Mastenbroek \etal~\cite{DBLP:conf/ccgrid/MastenbroekAJLB21}. In order to narrow the scope of the project, we only consider {OpenDC} as a simulator for the digital twin design. @@ -54,11 +87,10 @@ A failure model consists of two statistical distributions: \item to model service unavailability \item to model service availability. \end{enumerate*} -A failure trace is defined by an interval, duration, and intensity of several failures, which are later looped throughout the simulated workload (source \url{opendc.org}). +A failure trace is defined by an interval, duration, and intensity of several failures, which are later looped throughout the simulated workload~\cite{GitHub:software/OpenDC}. In summary OpenDC enables experimentation with failures that enables insights that are not provided by other state-of-the-art software. However, the fidelity of failure modeling inside a datacenter simulation is still insufficient to predict in failures in real-time, as they happen in a physical datacenter. Since a datacenter simulator is quite different from a digital twin, we cannot use the same computation methods from simulation to predict real-time failures. -Digital twinning is an improvement upon pure simulation. \begin{figure}[t] \centering \includegraphics[width=0.95\linewidth]{images/five_dimensional_dt.pdf} @@ -225,7 +257,7 @@ Kalibre takes the best of both \gls{ml} and \gls{cfd} approaches and achieves su \begin{figure}[t] \centering - \includegraphics[width=0.95\linewidth]{images/system_model.pdf} + \includegraphics[width=0.95\linewidth]{images/system_model.png} \caption[A system model for datacenter digital twins.]{A generic system model for datacenter digital twin deployments. The design of DyTwin~\cite{DBLP:conf/sc/TaheriBPRHDEWPM24} indirectly incorporates in its architecture a ``virtual-to-virtual`` digital thread between different digital twins. Zhao \etal likewise present key elements to the digital thread in their architecture~\cite{DBLP:conf/AppliedEnergy/Zhao20}. We add the \emph{Digital Thread} to our model explicitly.} |