-The NAS parallel benchmarks were executed again over processors that follow the the new power scenarios.
-The class C of each benchmark was run over 8 or 9 nodes and the results are presented in tables
-(\ref{table:res_s1} and \ref{table:res_s2}). These tables show that the energy saving percentage of the 70\%-30\%
-scenario is less for all benchmarks compared to the energy saving of the 90\%-10\% scenario. Indeed, in the latter
-more dynamic power is consumed when nodes are running on their maximum frequencies, thus, scaling down the frequency
-of the nodes results in higher energy savings than in the 70\%-30\% scenario. On the other hand, the performance
-degradation percentage is less in the 70\%-30\% scenario compared to the 90\%-10\% scenario. This is due to the
-higher static power percentage in the first scenario which makes it more relevant in the overall consumed energy.
-Indeed, the static energy is related to the execution time and if the performance is degraded the total consumed
-static energy is directly increased. Therefore, the proposed algorithm do not scales down much the frequencies of the
-nodes in order to limit the increase of the execution time and thus limiting the effect of the consumed static energy .
-
-The two new power scenarios are compared to the old one in figure (\ref{fig:sen_comp}). It shows the average of
-the performance degradation, the energy saving and the distances for all NAS benchmarks of class C running on 8 or 9 nodes.
-The comparison shows that the energy saving ratio is proportional to the dynamic power ratio: it is increased
-when applying the 90\%-10\% scenario because at maximum frequency the dynamic energy is the the most relevant
-in the overall consumed energy and can be reduced by lowering the frequency of some processors. On the other hand,
-the energy saving is decreased when the 70\%-30\% scenario is used because the dynamic energy is less relevant in
-the overall consumed energy and lowering the frequency do not returns big energy savings.
-Moreover, the average of the performance degradation is decreased when using a higher ratio for static power
-(e.g. 70\%-30\% scenario and 80\%-20\% scenario). Since the proposed algorithm optimizes the energy consumption
-when using a higher ratio for dynamic power the algorithm selects bigger frequency scaling factors that result in
-more energy saving but less performance, for example see the figure (\ref{fig:scales_comp}). The opposite happens
-when using a higher ratio for static power, the algorithm proportionally selects smaller scaling values which
-results in less energy saving but less performance degradation.
-
-
- \begin{table}[htb]
- \caption{The results of 70\%-30\% powers scenario}
+The NAS parallel benchmarks were executed again over processors that follow the
+new power scenarios. The class C of each benchmark was run over 8 or 9 nodes
+and the results are presented in Tables~\ref{table:res_s1} and
+\ref{table:res_s2}. These tables show that the energy saving percentage of the
+\np[\%]{70}-\np[\%]{30} scenario is smaller for all benchmarks compared to the
+energy saving of the \np[\%]{90}-\np[\%]{10} scenario. Indeed, in the latter
+more dynamic power is consumed when nodes are running on their maximum
+frequencies, thus, scaling down the frequency of the nodes results in higher
+energy savings than in the \np[\%]{70}-\np[\%]{30} scenario. On the other hand,
+the performance degradation percentage is smaller in the \np[\%]{70}-\np[\%]{30}
+scenario compared to the \np[\%]{90}-\np[\%]{10} scenario. This is due to the
+higher static power percentage in the first scenario which makes it more
+relevant in the overall consumed energy. Indeed, the static energy is related
+to the execution time and if the performance is degraded the amount of consumed
+static energy directly increases. Therefore, the proposed algorithm does not
+really significantly scale down much the frequencies of the nodes in order to
+limit the increase of the execution time and thus limiting the effect of the
+consumed static energy.
+
+Both new power scenarios are compared to the old one in
+Figure~\ref{fig:sen_comp}. It shows the average of the performance degradation,
+the energy saving and the distances for all NAS benchmarks of class C running on
+8 or 9 nodes. The comparison shows that the energy saving ratio is proportional
+to the dynamic power ratio: it is increased when applying the
+\np[\%]{90}-\np[\%]{10} scenario because at maximum frequency the dynamic energy
+is the most relevant in the overall consumed energy and can be reduced by
+lowering the frequency of some processors. On the other hand, the energy saving
+decreases when the \np[\%]{70}-\np[\%]{30} scenario is used because the dynamic
+energy is less relevant in the overall consumed energy and lowering the
+frequency does not return big energy savings. Moreover, the average of the
+performance degradation is decreased when using a higher ratio for static power
+(e.g. \np[\%]{70}-\np[\%]{30} scenario and \np[\%]{80}-\np[\%]{20}
+scenario). Since the proposed algorithm optimizes the energy consumption when
+using a higher ratio for dynamic power the algorithm selects bigger frequency
+scaling factors that result in more energy saving but less performance, for
+example see Figure~\ref{fig:scales_comp}. The opposite happens when using a
+higher ratio for static power, the algorithm proportionally selects smaller
+scaling values which result in less energy saving but also less performance
+degradation.
+
+
+ \begin{table}[!t]
+ \caption{The results of the \np[\%]{70}-\np[\%]{30} power scenario}