efficiency and relevance of our approach, using the discrete event
simulator OMNeT++ \cite{varga}. We performed simulations for five
different densities varying from 50 to 250~nodes. Experimental results
efficiency and relevance of our approach, using the discrete event
simulator OMNeT++ \cite{varga}. We performed simulations for five
different densities varying from 50 to 250~nodes. Experimental results
the sensing period which will have a duration of 60 seconds. Thus, an
active node will consume 12~joules during sensing phase, while a
sleeping node will use 0.002 joules. Each sensor node will not
the sensing period which will have a duration of 60 seconds. Thus, an
active node will consume 12~joules during sensing phase, while a
sleeping node will use 0.002 joules. Each sensor node will not
joules. In all experiments the parameters are set as follows:
$R_s=5m$, $w_{\Theta}=1$, and $w_{U}=|P^2|$.
joules. In all experiments the parameters are set as follows:
$R_s=5m$, $w_{\Theta}=1$, and $w_{U}=|P^2|$.
for the three approaches. It can be seen that the three approaches
give similar coverage ratios during the first rounds. From the
9th~round the coverage ratio decreases continuously with the simple
for the three approaches. It can be seen that the three approaches
give similar coverage ratios during the first rounds. From the
9th~round the coverage ratio decreases continuously with the simple
$90\%$ for five more rounds. Coverage ratio decreases when the number
of rounds increases due to dead nodes. Although some nodes are dead,
thanks to strategy~1 or~2, other nodes are preserved to ensure the
$90\%$ for five more rounds. Coverage ratio decreases when the number
of rounds increases due to dead nodes. Although some nodes are dead,
thanks to strategy~1 or~2, other nodes are preserved to ensure the
the second strategy, because the global optimization permit to turn
off more sensors. Indeed, when there are two subregions more nodes
remain awake near the border shared by them. Note that again as the
the second strategy, because the global optimization permit to turn
off more sensors. Indeed, when there are two subregions more nodes
remain awake near the border shared by them. Note that again as the
performing, since its takes longer to have the two subregion networks
simultaneously disconnected.
\subsection{The Network Lifetime}
We have defined the network lifetime as the time until all nodes have
performing, since its takes longer to have the two subregion networks
simultaneously disconnected.
\subsection{The Network Lifetime}
We have defined the network lifetime as the time until all nodes have
becomes disconnected. In figure~\ref{fig6}, the network lifetime for
different network sizes and for the three approaches is illustrated.
becomes disconnected. In figure~\ref{fig6}, the network lifetime for
different network sizes and for the three approaches is illustrated.
increases when the size of the network increase, with our approaches
that lead to the larger lifetime improvement. By choosing for each
round the well suited nodes to cover the region of interest and by
increases when the size of the network increase, with our approaches
that lead to the larger lifetime improvement. By choosing for each
round the well suited nodes to cover the region of interest and by
-that the larger the sensor number, the more our strategies outperform
-the heuristic. Strategy~2, which uses two leaders, is the best one
+that the larger the sensor number is, the more our strategies outperform
+the simple heuristic. Strategy~2, which uses two leaders, is the best one
because it is robust to network disconnection in one subregion. It
also means that distributing the algorithm in each node and
subdividing the sensing field into many subregions, which are managed
because it is robust to network disconnection in one subregion. It
also means that distributing the algorithm in each node and
subdividing the sensing field into many subregions, which are managed