takes \np[ms]{0.04} on average for 4 nodes and \np[ms]{0.15} on average for 144
nodes. The algorithm complexity is $O(F\cdot (N \cdot4) )$, where $F$ is the
number of iterations and $N$ is the number of computing nodes. The algorithm
-needs on average from 12 to 20 iterations to selects the best vector of frequency scaling factors that give the results of the next section. \textbf{put the lst paragraph in experiments}
-
+needs on average from 12 to 20 iterations to selects the best vector of frequency scaling factors that give the results of the next section.
+Therefore, there is a small distance between the energy and
+the performance curves in a homogeneous cluster compare to heterogeneous one, for example see the figure(\ref{fig:r1}) and figure(\ref{fig:r2}) . Then the
+algorithm starts to search for the optimal vector of the frequency scaling factors from the selected initial
+frequencies until all node reach their minimum frequencies.
+\begin{figure}[t]
+ \centering
+ \includegraphics[scale=0.5]{fig/start_freq}
+ \caption{Selecting the initial frequencies}
+ \label{fig:st_freq}
+\end{figure}