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diff --git a/content/background.tex b/content/background.tex index 97dc6aa..68ce6a2 100644 --- a/content/background.tex +++ b/content/background.tex @@ -47,31 +47,7 @@ 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}. -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. -We decided to use {OpenDC}, because we find it important for a simulator to model hardware failures well. -\emph{Failure models} are a carefully calibrated, advanced feature of {OpenDC}. -Further details about {OpenDC} can be referred to in the linked literature \cite{DBLP:conf/ccgrid/MastenbroekAJLB21}. - -\subsection{Compute Failures}\label{sss:failures} +\section{Compute Failures}\label{sss:failures} A failure is defined as ``an event that makes a system fail to operate according to its specifications``~\cite{DBLP:journals/jpdc/JavadiKIE13}. A simple example of a failure is when an old hard drive stops working. Data on the disk is lost, and services running on the respective server are disrupted. @@ -99,10 +75,35 @@ A failure trace is defined by an interval, duration, and intensity of several fa 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. +\section{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}. +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. +We decided to use {OpenDC}, because we find it important for a simulator to model hardware failures well. +\emph{Failure models} are a carefully calibrated, advanced feature of {OpenDC}. +Further details about {OpenDC} can be referred to in the linked literature \cite{DBLP:conf/ccgrid/MastenbroekAJLB21}. + \begin{figure}[t] \centering \includegraphics[width=0.95\linewidth]{images/five_dimensional_dt.png} - \caption[A basic framework for the \gls{dt}.]{A basic framework for the \gls{dt}. Four core elements of a \gls{dt} are defined: The physical entity (\myCircled{1}) and the simulated virtual twin (\myCircled{2}). A service for out-of-band data analytics (\myCircled{3}) and a persistent storage of historical data (\myCircled{4}) are crucial to the \gls{dt} because they are necessary to gain meaningful monitoring insights. Adapted from Tao \etal ~\cite{DBLP:conf/cirp/TAO2018169}.} + \caption[A basic framework for the Digital Twin.]{A basic framework for the \gls{dt}. Four core elements of a \gls{dt} are defined: The physical entity (\myCircled{1}) and the simulated virtual twin (\myCircled{2}). A service for out-of-band data analytics (\myCircled{3}) and a persistent storage of historical data (\myCircled{4}) are crucial to the \gls{dt} because they are necessary to gain meaningful monitoring insights. Adapted from Tao \etal ~\cite{DBLP:conf/cirp/TAO2018169}.} + %Fei Tao is a renowned figure with over 62k citations. He is a figure of authority on digital twins.% \label{fig:five_dimensional_dt} \end{figure} |