From: Arnaud Giersch Date: Fri, 5 Apr 2013 13:25:38 +0000 (+0200) Subject: Define macros for the names "best effort" and "Makhoul". X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/loba-papers.git/commitdiff_plain/1d15a8ec249a5c61c46650801704389dcb00dbf6?ds=inline Define macros for the names "best effort" and "Makhoul". --- diff --git a/loba-besteffort/loba-besteffort.tex b/loba-besteffort/loba-besteffort.tex index 23fe6ea..36b1fbe 100644 --- a/loba-besteffort/loba-besteffort.tex +++ b/loba-besteffort/loba-besteffort.tex @@ -27,6 +27,9 @@ \newcommand{\VAR}[1]{\textit{#1}} +\newcommand{\besteffort}{\emph{best effort}} +\newcommand{\makhoul}{\emph{Makhoul}} + \begin{document} \begin{frontmatter} @@ -54,7 +57,7 @@ the most well known algorithm for which the convergence proof is given. From a practical point of view, when a node wants to balance a part of its load to some of its neighbors, the strategy is not described. In this paper, we - propose a strategy called \emph{best effort} which tries to balance the load + propose a strategy called \besteffort{} which tries to balance the load of a node to all its less loaded neighbors while ensuring that all the nodes concerned by the load balancing phase have the same amount of load. Moreover, asynchronous iterative algorithms in which an asynchronous load balancing @@ -101,7 +104,7 @@ Although the Bertsekas and Tsitsiklis' algorithm describes the condition to ensure the convergence, there is no indication or strategy to really implement the load distribution. In other word, a node can send a part of its load to one or many of its neighbors while all the convergence conditions are -followed. Consequently, we propose a new strategy called \emph{best effort} +followed. Consequently, we propose a new strategy called \besteffort{} that tries to balance the load of a node to all its less loaded neighbors while ensuring that all the nodes concerned by the load balancing phase have the same amount of load. Moreover, when real asynchronous applications are considered, @@ -210,12 +213,12 @@ algorithm. \label{sec.besteffort} In this section we describe a new load-balancing strategy that we call -\emph{best effort}. First, we explain the general idea behind this strategy, +\besteffort{}. First, we explain the general idea behind this strategy, and then we describe some variants of this basic strategy. \subsection{Basic strategy} -The general idea behind the \emph{best effort} strategy is that each processor, +The general idea behind the \besteffort{} strategy is that each processor, that detects it has more load than some of its neighbors, sends some load to the most of its less loaded neighbors, doing its best to reach the equilibrium between those neighbors and himself. @@ -289,7 +292,7 @@ Section~\ref{sec.results}. The amount of data to send is then $s_{ij}(t) = Another load balancing strategy, working under the same conditions, was previously developed by Bahi, Giersch, and Makhoul in \cite{bahi+giersch+makhoul.2008.scalable}. In order to assess the performances -of the new \emph{best effort}, we naturally chose to compare it to this anterior +of the new \besteffort{}, we naturally chose to compare it to this anterior work. More precisely, we will use the algorithm~2 from \cite{bahi+giersch+makhoul.2008.scalable} and, in the following, we will reference it under the name of Makhoul's. @@ -501,7 +504,7 @@ we will describe in this section. \subsubsection{Load balancing strategies} Several load balancing strategies were compared. We ran the experiments with -the \emph{Best effort}, and with the \emph{Makhoul} strategies. \emph{Best +the \besteffort{}, and with the \makhoul{} strategies. \emph{Best effort} was tested with parameter $k = 1$, $k = 2$, and $k = 4$. Secondly, each strategy was run in its two variants: with, and without the management of \emph{virtual load}. Finally, we tested each configuration with \emph{real}, @@ -509,7 +512,7 @@ and with \emph{integer} load. To summarize the different load balancing strategies, we have: \begin{description} -\item[\textbf{strategies:}] \emph{Makhoul}, or \emph{Best effort} with $k\in +\item[\textbf{strategies:}] \makhoul{}, or \besteffort{} with $k\in \{1,2,4\}$ \item[\textbf{variants:}] with, or without virtual load \item[\textbf{domain:}] real load, or integer load @@ -716,10 +719,10 @@ allocated time, or because we simply decided not to run it. \FIXME{annoncer le plan de la suite} -\subsubsection{The \emph{best effort} strategy} +\subsubsection{The \besteffort{} strategy} Looking at the graph on figure~\ref{fig.results1}, we can see that the -\emph{best effort} strategy is not too bad. +\besteffort{} strategy is not too bad, compared to the \makhoul{} strategy. \FIXME{donner les premières conclusions} \FIXME{comparer be/makhoul -> be tient la route (parler du cas réel uniquement)}