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\documentclass{beamer}
\usepackage{graphics}
%Information to be included in the title page:
\title{Nodes data dissemination policy prediction under energy consumption and network coverage constraints}
\author{Loic Guegan, Issam Raïs}
\institute{UiT}
\date{2022}
\setbeamertemplate{navigation symbols}{}
\begin{document}
\frame{\titlepage}
\begin{frame}
\frametitle{Context}
Disseminate data:
\begin{itemize}
\setlength\itemsep{0.8em}
\item Wireless communications
\item Energy constraint
\item Harsh environment
\end{itemize}
\vspace{1cm}
\centering
\textbf{But energy and coverage not deterministic}
\end{frame}
\begin{frame}
\frametitle{Problem}
\includegraphics[trim={0 10cm 30cm 0},scale=0.3,clip]{../analysis/figures/dimension_energy-coverage.pdf}
\end{frame}
\begin{frame}
\frametitle{Problem}
\textbf{How to choose the right configuration for a given setup?}\\
\vspace{1cm}
Knowing that:\\ \vspace{0.3cm}
\begin{itemize}
\item Perfect coverage not required:
\begin{itemize}
\item Just N+1,...,N+n redundancy (so n network coverage)
\item Collaboration of n nodes (say 3 to monitor some metrics)
\end{itemize}
\item Clear nodes energy budget
\end{itemize}
\end{frame}
\begin{frame}
\frametitle{Problem}
Knowing:
\begin{itemize}
\item Nodes setup:
\begin{itemize}
\item LoRa/NbIoT?
\item Uptimes duration 60s/180s?
\end{itemize}
\item Requirements:
\begin{itemize}
\item Nodes energy consumption
\item Network coverage
\end{itemize}
\end{itemize}
\vspace{1cm}
\centering
\textbf{How can we predict which policy to use to meet the requirements?}
\end{frame}
\begin{frame}
\frametitle{Solution}
\begin{centering}
\textbf{Use classification models!}
\end{centering}\\ \vspace{1cm}
We choose:
\begin{itemize}
\item K Nearrest Neighbours
\item Decision Trees
\end{itemize}
\vspace{1cm}
Two ML training approaches:
\begin{itemize}
\item Offline
\item Online
\end{itemize}
\end{frame}
\begin{frame}
\frametitle{Offline: The hint case}
\centering
\includegraphics[scale=0.35]{../analysis/figures/dimension_energy-coverage.pdf}
\end{frame}
\begin{frame}
\frametitle{Offline: Coverage}
\centering
\includegraphics[trim={0 0 20cm 0},scale=0.4,clip]{../analysis/figures/sim_dimension_coverage_WITH_HINT.pdf}
\end{frame}
\begin{frame}
\frametitle{Offline: Energy}
\centering
\includegraphics[trim={0 0 20cm 0},scale=0.4,clip]{../analysis/figures/sim_dimension_energy_WITH_HINT.pdf}
\end{frame}
\begin{frame}
\frametitle{Offline: Accuracy}
\begin{table}[!ht]
\centering
\resizebox{\columnwidth}{!}{%
\begin{tabular}{|l|l|l|l|l|l|}
\hline
\textbf{model} & f1\_baseline & f1\_hint & f1\_extended & f1\_hintandextended & accuracy \\ \hline
\textit{knn} & 0.88 & NA & 0.89 & 0.91 & 0.81 \\ \hline
\textit{tree} & 0.93 & NA & 0.86 & 0.92 & 0.83 \\ \hline
\end{tabular}}
\end{table}
\end{frame}
\begin{frame}
\frametitle{Online}
\centering
\includegraphics[scale=0.3]{../analysis/figures/months_knn.pdf}
\end{frame}
\begin{frame}
\frametitle{Contribution}
\begin{itemize}
\item Methodology
\item An offline model
\item A vision on how such model ML on an online ML scenario
\end{itemize}
\end{frame}
\end{document}
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