1 \documentclass[14]{article}
7 %\usepackage[T1]{fontenc}
8 %\usepackage[latin1]{inputenc}
10 \renewcommand{\labelenumii}{\labelenumi\arabic{enumii}}
11 %\titleformat*{\section}{\Large\bfseries}
13 %\title{Response to the reviewers of \bf "Perimeter-based Coverage Optimization to Improve Lifetime in Wireless Sensor Networks"}
14 %\author{Ali Kadhum Idrees, Karine Deschinkela, Michel Salomon and Raphael Couturier}
22 \vspace{-0.5cm}\hspace{-2cm}FEMTO-ST Institute, UMR 6714 CNRS
24 \hspace{-2cm}University Bourgogne Franche-Comt\'e
26 \hspace{-2cm}IUT Belfort-Montb\'eliard, BP 527, 90016 Belfort Cedex, France.
31 On the decision for the article
33 ``Multiround Distributed Lifetime Coverage Optimization \\ Protocol in Wireless
36 by Ali Kadhum Idrees, Karine Deschinkel, Michel Salomon, and Raph\"ael Couturier
42 \noindent Dear Editor,
44 After a careful reading of your last decision letter, we are quite disappointed
45 by the rejection of our article named: ``Multiround Distributed Lifetime
46 Coverage Optimization Protocol in Wireless Sensor Networks'', submitted for
47 publication in the AD HOC NETWORKS journal. Indeed, we have started the
48 submission process in September 2014 and obtained the comments of only ONE
49 reviewer in July 2015. Its suggestion were very helpful and we incorporated
50 them in the revised article submitted in September 2015.
52 In particular, we have stopped the resolution of the Branch-and-Bound
53 method after a time threshold empirically defined and we have retained
54 the best feasible solution found by the solver, as it was suggested by
55 the reviewer. We made our best to carefully address the issues raised
56 by the referee and revised our paper accordingly. So we would like to
57 clarify some of the points raised by the reviewer, since some them
58 seem to be irrelevant or unfair.
60 \noindent {\bf 1.} The authors have partially taken into account the comments
61 of my previous review. Additional content has been added, but these additions
62 are sometime confusing.\\
64 \textcolor{blue}{\textbf{\textsc{Answer:} The reviewer does not clearly indicate
65 which addition is confusing.}}\\
67 \noindent {\bf 2.} The answer that the authors have provided to my comments
68 should have been inserted into the paper, this is not always the case (i.e., my
69 comment about the duration of the rounds).\\
71 \textcolor{blue}{\textbf{\textsc{Answer:} We clearly indicated in Section~3.2
72 that the rounds are of equal duration and we explained that this parameter
73 should be set according to the types of application (see our
75 ``minor comments'' in our previous answer).}}\\
77 \noindent {\bf 3.} In Section~3.1, all nodes are assumed to be ``homogeneous
78 from the point of view of energy provision''. Why is such an hypothesis
79 necessary? This assumption is likely to be satisfied only when the WSN is
80 deployed for the first time, with new sensors. But after using the network for
81 the first time, the aforementioned hypothesis is not likely to be satisfied
84 \textcolor{blue}{\textbf{\textsc{Answer:} The reviewer might have misread
85 the sentence in Section~3.1: ``We assume that all nodes are {\bf
86 homogeneous} in terms of communication and processing capabilities, and
87 {\bf heterogeneous} from the point of view of energy provision.'' }}\\
89 \noindent {\bf 4.} The last paragraph of Section 3.1 is very confusing. It
90 seems that the author attempt to propose area coverage instead of target
91 coverage, but instead of defining ``primary points'' inside the area to be
92 covered, they define points inside the sensing range of the sensors, that are
93 obviously covered when the corresponding sensor is active. There exists works in
94 the literature for area coverage, the authors should read them.\\
96 \textcolor{blue}{\textbf{\textsc{Answer:} This remark is rather offensive. Of
97 course we have read the literature for area coverage. We have used the metric ``Coverage
98 Ratio'' (defined in Section~4.3) to measure how much of the area is covered.
99 But the optimization process to decide which sensor has to be active or not
100 in each round is based on the coverage of only a specified set of points
101 called primary points. So the area coverage problem is transformed into the
102 target coverage problem. So from our point of view, this remark is
105 \noindent {\bf 5.} In Section 3.2, the reason why a subregion is defined in such
106 a way that the distance between any two sensors in the same subregion is less
107 than 3 hops is not justified. The reader is not told if the proposed protocol
108 works better when the number of subregions is low or high. No algorithm for
109 defining the subregions is given. It pertains to a clustering problem, for which
110 a large number of algorithms exists, but without a sound definition of what is a
111 'good' partitioning for the proposed protocol, the reader cannot select a
112 clustering algorithm. \\
114 \textcolor{blue}{\textbf{\textsc{Answer:} The choice of the number of
115 subregions is discussed in the last paragraph of Section~4.2. More
116 particularly, we explain that this parameter should be chosen by taking into
117 account the trade-off between the benefit of the optimization problem
118 induced by the number of sensors in a subregion and the time needed to solve
119 it. As said at the beginning of Section~3.2, the area of interest is
120 ``divided into regular homogeneous subregions using a simple
121 divide-and-conquer algorithm.''}}\\
123 \noindent {\bf 6.} The ILP of Section 3.5 aims at addressing a bi-objective
124 problem. Since full coverage is required, the ILP should first ensure total
125 coverage, and then minimize overcoverage. The current ILP is not a proper
126 formulation for reaching this objective, as undercoverage can be compensated by
127 overcoverage. The primary and secondary objective are then mixed up into a
128 single objective function with no interpretable meaning. Of course, an objective
129 function value of 100 is better than an objective value of 101, but one cannot
130 tell if a gap of 1 makes a major difference or not. The objectives should be
131 distinguished, and the problem should be addressed as a multiobjective
132 optimization problem.\\
134 \textcolor{blue}{\textbf{\textsc{Answer:} As mentioned in the paper, the ILP of
135 Section~3.5 is based on the model proposed by F. Pedraza, A. L. Medaglia,
136 and A. Garcia (``Efficient coverage algorithms for wireless sensor
137 networks'') with some modifications. The originality of the model is to
138 solve both objectives in a parallel fashion: maximizing the coverage and
139 minimizing the overcoverage. Nevertheless the weights $w_\theta$ and $w_U$
140 must be properly chosen so as to guarantee that the number of points which
141 are covered during each round is maximum. By choosing $w_{U}$ much larger
142 than $w_{\theta}$, the coverage of a maximum of primary points is
143 ensured. Then for the same number of covered primary points, the solution
144 with a minimal number of active sensors is preferred. It has been formally
145 proven in the paper mentioned above that this guarantee is satisfied for a
146 constant weighting $w_{U}$ greater than $\left|P\right|$ (when $w_{\theta}$
150 \noindent {\bf 6.} The content of Section 4.3, where different metrics are
151 proposed to assess the solution quality, is a sign of an ill formulated problem:
152 how to comment on the performance of an algorithm on a criterion (say network
153 lifetime) if the ILP does not take this objective into account? The performances
154 with these additional objectives are likely to be related to the ILP solver
155 used: many optimal solutions to the ILP of Section 3 may have a very different
156 impact in terms of these additional metrics. Hence, measuring them is
159 \textcolor{blue}{\textbf{\textsc{Answer:} We disagree with this remark. It is quite
160 possible to optimize a criterion to have an impact on another one. In the
161 problem formulation proposed here, the number of active sensors is minimized
162 in each round for a maximal level of coverage. Limiting the activation time
163 of each sensor has a direct impact on its lifetime and consequently on the
164 network lifetime, as shown in our experimental results. For example, such an
165 idea is used in the models developed for brachytherapy treatment planning to
166 improve the quality of a dose distribution ("Comparison of inverse planning
167 simulated annealing and geometrical optimization for prostate high-dose-rate
168 brachytherapy", I-Chow J. Hsu1, E. Lessard, V. Weinberg, J. Pouliot, {\it
169 Brachytherapy} Volume 3, Issue 3, 2004, Pages 147-152): the objective in
170 the problem formulation is to minimize a weighted sum of the differences
171 between prescribed doses and obtained doses in reference points, whereas
172 many criteria (like dose-volume histograms, conformal index COIN) are used
173 for quantitative evaluation of dose plans.}}\\
174 %si vous avez d'autres exemples plus parlants?
176 We hope that these observations will allow you to revise your decision
177 concerning our manuscript. If possible, we would like to benefit
178 from the comments of an
