[sharelatex-git-integration Best effort strategy and virtual load for asynchronous...

[loba-papers.git] / loba-besteffort / loba-besteffort.tex

diff --git a/loba-besteffort/loba-besteffort.tex b/loba-besteffort/loba-besteffort.tex
index b95f6d5ee7dc9378b47c208a43c1cd71c37f7536..add4b8b1c2ad5cf091fd5f5fb91f9ae9b9a5813b 100644 (file)
--- a/loba-besteffort/loba-besteffort.tex
+++ b/loba-besteffort/loba-besteffort.tex
@@ -348,17 +348,14 @@ several of its neighbors, and then might temporary go off the equilibrium state.
 This is particularly true with strongly connected applications.
 
 
 This is particularly true with strongly connected applications.
 
 

-

 In order to reduce this effect, we add the ability to level the amount of loads to send.
 The idea, here, is to make as few steps as possible toward the equilibrium, such that a
 potentially unsuitable decision pointed above has a lower impact on the local equilibrium.
 In order to reduce this effect, we add the ability to level the amount of loads to send.
 The idea, here, is to make as few steps as possible toward the equilibrium, such that a
 potentially unsuitable decision pointed above has a lower impact on the local equilibrium.

-Roughly speaking, once $s_{ij}$ is estimated as previously explained, it is simply weighted by
-a given prescribed threshold parameter which we call 
-%.  This parameter is called 
-$k$ in
-Section~\ref{sec.results}.  The amount of data to send is then $s_{ij}(t) =
-(\bar{x} - x^i_j(t))/k$.
-%\FIXME[check that it's still named $k$ in Sec.~\ref{sec.results}]{}
+A weighting system parameter $k$ is introduced to orchestrate the right balance between the topology structure and the computation to communication ratios (CCR) values of the deployed application. Indeed, to speedup the convergence time of the load balancing process, one is faced with a difficult trade-off to choose an appropriate amount of load to send between node neighbors upon load imbalance detection. On the one hand, if $k$ is small, we expect faster convergence time for sparsely connected application and large CCR values. On the other hand, for strongly connected applications and small CCR values, a large value of $k$ will enable us to better balance the load locally and therefore minimize the number of iterations toward the global equilibrium. In the experiments section (Section~\ref{sec.results}), we observe that choosing $k$ in 1,2 or 4, leads to good results for the considered CCR values and the targeted topology structures.
+So the amount of data to send is then $s_{ij}(t) = (\bar{x} - x^i_j(t))/k$.
+
+
+

 
 
 
 
 
 


@@ -599,7 +596,7 @@ load units.
 
 For all the previous configurations, the
 computation and communication costs of a load unit are defined.  They were chosen so as to
 
 For all the previous configurations, the
 computation and communication costs of a load unit are defined.  They were chosen so as to

-have two different computation to communication ratios (CCR), and hence characterize 
+have two different CCR, and hence characterize 

 two different types of applications:
 \begin{itemize}
 \item mainly communicating, with a CCR of $1/10$;
 two different types of applications:
 \begin{itemize}
 \item mainly communicating, with a CCR of $1/10$;