-implemented PeCO protocol in OMNeT++~\citep{varga} simulator. Besides PeCO, two
-other protocols, described in the next paragraph, will be evaluated for
-comparison purposes. The simulations were run on a DELL laptop with an Intel
-Core~i3~2370~M (1.8~GHz) processor (2 cores) whose MIPS (Million Instructions
-Per Second) rate is equal to 35330. To be consistent with the use of a sensor
-node based on Atmels AVR ATmega103L microcontroller (6~MHz) having a MIPS rate
-equal to 6, the original execution time on the laptop is multiplied by 2944.2
-$\left(\frac{35330}{2} \times \frac{1}{6} \right)$. The modeling language for
-Mathematical Programming (AMPL)~\citep{AMPL} is employed to generate the integer
-program instance in a standard format, which is then read and solved by the
-optimization solver GLPK (GNU linear Programming Kit available in the public
-domain) \citep{glpk} through a Branch-and-Bound method.
-
-As said previously, the PeCO is compared to three other approaches. The first
-one, called DESK, is a fully distributed coverage algorithm proposed by
-\citep{ChinhVu}. The second one, called GAF~\citep{xu2001geography}, consists in
-dividing the monitoring area into fixed squares. Then, during the decision
-phase, in each square, one sensor is chosen to remain active during the sensing
-phase. The last one, the DiLCO protocol~\citep{Idrees2}, is an improved version
-of a research work we presented in~\citep{idrees2014coverage}. Let us notice that
-PeCO and DiLCO protocols are based on the same framework. In particular, the
-choice for the simulations of a partitioning in 16~subregions was made because
-it corresponds to the configuration producing the best results for DiLCO. The
-protocols are distinguished from one another by the formulation of the integer
-program providing the set of sensors which have to be activated in each sensing
-phase. DiLCO protocol tries to satisfy the coverage of a set of primary points,
-whereas the PeCO protocol objective is to reach a desired level of coverage for each
+implemented PeCO protocol in OMNeT++~\citep{varga} simulator. The simulations
+were run on a DELL laptop with an Intel Core~i3~2370~M (1.8~GHz) processor (2
+cores) whose MIPS (Million Instructions Per Second) rate is equal to 35330. To
+be consistent with the use of a sensor node based on Atmels AVR ATmega103L
+microcontroller (6~MHz) having a MIPS rate equal to 6, the original execution
+time on the laptop is multiplied by 2944.2 $\left(\frac{35330}{2} \times
+\frac{1}{6} \right)$. Energy consumption is calculated according to the power
+consumption values, in milliWatt per second, given in Table~\ref{tab:EC}
+based on the energy model proposed in \citep{ChinhVu}.
+
+% Questions on energy consumption calculation
+% 1 - How did you compute the value for COMPUTATION status ?
+% 2 - I have checked the paper of Chinh T. Vu (2006) and I wonder
+% why you completely deleted the energy due to the sensing range ?
+% => You should have use a fixed value for the sensing rangge Rs (5 meter)
+% => for all the nodes to compute f(Ri), which would have lead to energy values
+
+\begin{table}[h]
+\centering
+\caption{Energy consumption}
+\label{tab:EC}
+\begin{tabular}{|l||cccc|}
+ \hline
+ {\bf Sensor status} & MCU & Radio & Sensor & {\it Power (mW)} \\
+ \hline
+ LISTENING & On & On & On & 20.05 \\
+ ACTIVE & On & Off & On & 9.72 \\
+ SLEEP & Off & Off & Off & 0.02 \\
+ COMPUTATION & On & On & On & 26.83 \\
+ \hline
+ \multicolumn{4}{|l}{Energy needed to send or receive a 2-bit content message} & 0.515 \\
+ \hline
+\end{tabular}
+\end{table}
+
+The modeling language for Mathematical Programming (AMPL)~\citep{AMPL} is used
+to generate the integer program instance in a standard format, which is then
+read and solved by the optimization solver GLPK (GNU linear Programming Kit
+available in the public domain) \citep{glpk} through a Branch-and-Bound method.
+
+% No discussion about the execution of GLPK on a sensor ?
+
+Besides PeCO, three other protocols will be evaluated for comparison
+purposes. The first one, called DESK, is a fully distributed coverage algorithm
+proposed by \citep{ChinhVu}. The second one, called
+GAF~\citep{xu2001geography}, consists in dividing the monitoring area into fixed
+squares. Then, during the decision phase, in each square, one sensor is chosen
+to remain active during the sensing phase. The last one, the DiLCO
+protocol~\citep{Idrees2}, is an improved version of a research work we presented
+in~\citep{idrees2014coverage}. Let us notice that PeCO and DiLCO protocols are
+based on the same framework. In particular, the choice for the simulations of a
+partitioning in 16~subregions was made because it corresponds to the
+configuration producing the best results for DiLCO. The protocols are
+distinguished from one another by the formulation of the integer program
+providing the set of sensors which have to be activated in each sensing
+phase. DiLCO protocol tries to satisfy the coverage of a set of primary points,
+whereas PeCO protocol objective is to reach a desired level of coverage for each
