each time 25~randomly generated networks. The nodes are deployed on a field of
interest of $(50 \times 25)~m^2 $ in such a way that they cover the field with a
high coverage ratio. Each node has an initial energy level, in Joules, which is
-randomly drawn in the interval $[500-700]$. If it's energy provision reaches a
+randomly drawn in the interval $[500-700]$. If its energy provision reaches a
value below the threshold $E_{th}=36$~Joules, the minimum energy needed for a
node to stay active during one period, it will no more participate in the
coverage task. This value corresponds to the energy needed by the sensing phase,
\cite{ChinhVu}. The second one, called GAF~\cite{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
+%%RC can we download DILCO?
phase. The last one, the DiLCO protocol~\cite{Idrees2}, is an improved version
of a research work we presented in~\cite{idrees2014coverage}. Let us notice that
LiCO and DiLCO protocols are based on the same framework. In particular, the
increases with the size of the network, and it is clearly the larger for DiLCO
and LiCO protocols. For instance, for a network of 300~sensors and coverage
ratio greater than 50\%, we can see on Figure~\ref{fig3LT}(b) that the lifetime
-is about two times longer with LiCO compared to DESK protocol. The performance
+is about twice longer with LiCO compared to DESK protocol. The performance
difference is more obvious in Figure~\ref{fig3LT}(b) than in
Figure~\ref{fig3LT}(a) because the gain induced by our protocols increases with
the time, and the lifetime with a coverage of 50\% is far more longer than with
\label{sec:Conclusion and Future Works}
In this paper we have studied the problem of lifetime coverage optimization in
-WSNs. We designed a new protocol, called Lifetime Coverage Optimization, which
+WSNs. We have designed a new protocol, called Lifetime Coverage Optimization, which
schedules nodes' activities (wake up and sleep stages) with the objective of
maintaining a good coverage ratio while maximizing the network lifetime. This
protocol is applied in a distributed way in regular subregions obtained after
%periods, each period consists of four stages: (i) Information Exchange,
%(ii) Leader Election, (iii) a Decision based new optimization model in order to
%select the nodes remaining active for the last stage, and (iv) Sensing.
-We carried out several simulations to evaluate the proposed protocol. The
+We have carried out several simulations to evaluate the proposed protocol. The
simulation results show that LiCO is more energy-efficient than other
approaches, with respect to lifetime, coverage ratio, active sensors ratio, and
energy consumption.
\noindent As a Ph.D. student, Ali Kadhum IDREES would like to gratefully
acknowledge the University of Babylon - IRAQ for financial support and Campus
-France for the received support. This work has also been supported by the Labex
-ACTION.
+France for the received support. This work is also partially funded by the Labex ACTION program (contract ANR-11-LABX-01-01).
+
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