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10 \title{Best effort strategy and virtual load for asynchronous iterative load balancing}
12 \author{Raphaël Couturier \and
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19 Tel.: +123-45-678910\\
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33 Most of the time, asynchronous load balancing algorithms have extensively been
34 studied in a theoretical point of view. The Bertsekas and Tsitsiklis'
35 algorithm~\cite[section~7.4]{bertsekas+tsitsiklis.1997.parallel}
36 is certainly the most well known algorithm for which the convergence proof is
37 given. From a practical point of view, when a node wants to balance a part of
38 its load to some of its neighbors, the strategy is not described. In this
39 paper, we propose a strategy called \texttt{best effort} which tries to balance
40 the load of a node to all its less loaded neighbors while ensuring that all the
41 nodes concerned by the load balancing phase have the same amount of load.
42 Moreover, asynchronous iterative algorithms in which an asynchronous load
43 balancing algorithm is implemented most of the time can dissociate messages
44 concerning load transfers and message concerning load information. In order to
45 increase the converge of a load balancing algorithm, we propose a simple
46 heuristic called \texttt{virtual load} which allows a node that receives an load
47 information message to integrate the load that it will receive later in its
48 load (virtually) and consequently sends a (real) part of its load to some of its
49 neighbors. In order to validate our approaches, we have defined a simulator
50 based on SimGrid which allowed us to conduct many experiments.
57 Load balancing algorithms are extensively used in parallel and distributed
58 applications in order to reduce the execution times. They can be applied in
59 different scientific fields from high performance computation to micro sensor
60 networks. They are iterative by nature. In literature many kinds of load
61 balancing algorithms have been studied. They can be classified according
62 different criteria: centralized or decentralized, in static or dynamic
63 environment, with homogeneous or heterogeneous load, using synchronous or
64 asynchronous iterations, with a static topology or a dynamic one which evolves
65 during time. In this work, we focus on asynchronous load balancing algorithms
66 where computer nodes are considered homogeneous and with homogeneous load with
67 no external load. In this context, Bertsekas and Tsitsiklis have proposed an
68 algorithm which is definitively a reference for many works. In their work, they
69 proved that under classical hypotheses of asynchronous iterative algorithms and
70 a special constraint avoiding \texttt{ping-pong} effect, an asynchronous
71 iterative algorithm converge to the uniform load distribution. This work has
72 been extended by many authors. For example,
73 DASUD~\cite{cortes+ripoll+cedo+al.2002.asynchronous} propose a version working
77 \bibliographystyle{spmpsci}
85 %%% ispell-local-dictionary: "american"
88 % LocalWords: Raphaël Couturier Arnaud Giersch Abderrahmane Sider
89 % LocalWords: Bertsekas Tsitsiklis SimGrid DASUD