From: Raphael Couturier Date: Wed, 30 Mar 2011 15:40:58 +0000 (+0200) Subject: new X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/loba-papers.git/commitdiff_plain/6c1cecf2bb25b10891ecfd5789373be5ad294ce4?ds=inline new --- diff --git a/supercomp11/supercomp11.tex b/supercomp11/supercomp11.tex index 7daaa52..7840e92 100644 --- a/supercomp11/supercomp11.tex +++ b/supercomp11/supercomp11.tex @@ -28,31 +28,45 @@ \begin{abstract} Most of the time, asynchronous load balancing algorithms have extensively been -studied in a theoretical point of view. The Bertsekas' algorithm is certainly -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 \texttt{best effort} 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 algorithm is -implemented most of the time can dissociate messages concerning load transfers -and message concerning load information. In order to increase the converge of a -load balancing algorithm, we propose a simple heuristic called \texttt{virtual - load} which allows a node that receives an load information message to -integrate the load that it will receive latter in its load (virtually) and -consequently sends a (real) part of its load to some of its neighbors. In order -to validate our approaches, we have defined a simulator based on SimGrid which -allowed us to conduct many experiments. +studied in a theoretical point of view. The Bertsekas and Tsitsiklis' algorithm +is certainly 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 \texttt{best effort} 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 algorithm is implemented most of the time can dissociate messages +concerning load transfers and message concerning load information. In order to +increase the converge of a load balancing algorithm, we propose a simple +heuristic called \texttt{virtual load} which allows a node that receives an load +information message to integrate the load that it will receive latter in its +load (virtually) and consequently sends a (real) part of its load to some of its +neighbors. In order to validate our approaches, we have defined a simulator +based on SimGrid which allowed us to conduct many experiments. \end{abstract} - -qsdqsd - +Load balancing algorithms are extensively used in parallel and distributed +applications in order to reduce the execution times. They can be applied in +different scientific fields from high performance computation to micro sensor +networks. They are iterative by nature. In literature many kinds of load +balancing algorithms have been studied. They can be classified according +different criteria: centralized or decentralized, in static or dynamic +environment, with homogeneous or heterogeneous load, using synchronous or +asynchronous iterations, with a static topology or a dynamic one which evolves +during time. In this work, we focus on asynchronous load balancing algorithms +where computer nodes are considered homogeneous and with homogeneous load with +no external load. In this context, Bertsekas and Tsitsiklis have proposed an +algorithm which is definitively a reference for many works. In their work, they +proved that under classical hypotheses of asynchronous iterative algorithms and +a special constraint avoiding \texttt{ping-pong} effect, an asynchronous +iterative algorithm converge to the uniform load distribution. This work has +been extended by many authors. For example, DASUD propose a version working with +integer load.