Dear Editor and Reviewers,
-First of all, we would like to thank you very much for your kind help to improve
-our article named: `` Multiround Distributed Lifetime Coverage Optimization
-Protocol in Wireless Sensor Networks ''. We highly appreciate the detailed
-valuable comments of the reviewers on our article. The suggestions are quite
-helpful for us and we incorporate them in the revised article. We are happy to
-submit to you a revised version that considers most of your remarks and
-suggestions to improve the quality of our article.
-
-As below, we would like to clarify some of the points raised by the reviewers
+First of all, we would like to thank you very much for your kind help in
+improving our article named: `` Multiround Distributed Lifetime Coverage
+Optimization Protocol in Wireless Sensor Networks ''. We highly appreciate the
+detailed and valuable comments of the reviewers on our article. The suggestions
+have been very helpful to us and we have incorporated them in the revised
+article. We are happy to submit to you a revised version that considers most of
+your remarks and suggestions to improve the quality of our article.
+
+Below, we would like to clarify some of the points raised by the reviewers
and we hope the reviewers and the editors will be satisfied by our responses to
the comments and the revision for the original manuscript.
\textcolor{blue}{\textbf{\textsc{Answer:} In our work, we assume that the
sensors are deployed almost uniformly and with high density over the region.
So we only need to fix a regular division of the region into subregions to
- make the problem tractable. The subdivision is made such that the number of
+ make the problem tractable. The subdivision has been made so that the number of
hops between any pairs of sensors inside a subregion is less than or equal
to~3.
% In particular, we discuss the number of subregions in......
\textcolor{blue}{\textbf{\textsc{Answer:} As mentioned in the paper the integer
program is based on the model proposed by F. Pedraza, A. L. Medaglia, and
A. Garcia (``Efficient coverage algorithms for wireless sensor networks'')
- with some modifications. Their initial approach consisted in first finding
- the maximum coverage obtainable using the available sensors and then to use
+ with some modifications. Their initial approach consisted first in finding
+ the maximum coverage obtainable using the available sensors and then in using
this information as input to the problem of minimizing the overcoverage. But
this two-steps approach is time consuming. The originality of the model is
to solve both objectives in a parallel fashion. Nevertheless the weights
$W_\theta$ and $W_U$ must be properly chosen so as to guarantee that the
maximum number of points which are covered during each round is maximum. By
- choosing $W_{U}$ very large compared to $W_{\theta}$, the coverage of a
- maximum of primary points is ensured. Then for a same number of covered
+ choosing $W_{U}$ much larger than $W_{\theta}$, the coverage of a
+ maximum of primary points is ensured. Then for the same number of covered
primary points, the solution with a minimal number of active sensors is
preferred. }}\\
tree. Therefore we conducted new simulations by applying your idea. That is
to say we have stopped the resolution of the Branch-and-Bound method after a
time threshold empirically defined and we retain the best feasible solution
- found by the solver. This approach allows to improve significantly the
+ found by the solver. This approach allows to significantly improve the
results with multirounds, especially for MuDiLCO-7, as shown in the paper.}}
\bigskip
the paper is organized as follows'' should mention the content of Section 5.
} \\
- \textcolor{blue}{\textbf{\textsc{Answer:} Right, fixed. Section 5 is included
- as subsection 4.5 within section 4.}}\\
+ \textcolor{blue}{\textbf{\textsc{Answer:} Right, fixed.}}\\
\noindent {\ding{90} Page 3 The sentence ``the centralized approaches usually
suffer from the scalability problem, making them less competitive as the
should provide at least one reference about the aforementioned study.}\\
\textcolor{blue}{\textbf{\textsc{Answer:} Right. We have included a section
- (section~4.4) dedicated to the choice and the number of primary points.}}\\
+ (section~5.1) dedicated to the choice and the number of primary points.}}\\
\noindent {\ding{90} Page 6, Figure 1: All rounds seem to have the same
duration. This should be stated explicitly, and justified (in column
is explicitly explained in the second paragraph of section~3.2. This
assumption leads to an integer formulation of the optimization problem. The
decision variables are binary variables, $X_{t,j}$ for the activation
- ($X_{t,j}=1$) or not ($X_{t,j}=0$) of the sensor $j$ during the round $t$.
+ ($X_{t,j}=1$) or not ($X_{t,j}=0$) of the sensor $j$ during round $t$.
Column generation based approaches can be applied when the decision
variables of the optimization problem are continuous. In this case the
variables are the time intervals during which the sensors of a cover set
with the types of applications, with the amount of initial energy in sensors
batteries, and also with the duration of the exchange phase. All
applications do not have the same Quality of Service requirements. In our
- case, information exchange is executed every hour, but the length of the
+ case, the information exchange is executed every hour, but the length of the
sensing period could be reduced and adapted dynamically. On the one hand, a
small sensing period would allow the network to be more reliable but would
have higher communication costs. On the other hand, the choice of a long
- duration may cause problems in case of nodes failure during the sensing
+ duration may cause problems in case of node failures during the sensing
period.}}\\
\noindent {\ding{90} Page 11 in Table 1 $W_\Theta$ should be replaced with
