of sensor node activity is planned for each subregion. The proposed
scheduling considers rounds during which a small number of nodes,
remaining active for sensing, is selected to ensure coverage. Each
-round consists of four phases: (i)~Information Exchange, (ii)~Leader
+round consists in four phases: (i)~Information Exchange, (ii)~Leader
Election, (iii)~Decision, and (iv)~Sensing. The decision process is
carried out by a leader node, which solves an integer program.
Simulation results show that the proposed approach can prolong the
for applications. Indeed, sensors nodes have limited resources in
terms of memory, energy and computational power.
-Since sensor nodes have limited battery life and without being able to
+Since sensor nodes have limited battery life and since it is impossible to
replace batteries, especially in remote and hostile environments, it
is desirable that a WSN should be deployed with high density because
spatial redundancy can then be exploited to increase the lifetime of
different sensors.
The works presented in \cite{Bang, Zhixin, Zhang} focus on the
-definition of a coverage-aware, distributed energy-efficient and
+definition of coverage-aware, distributed energy-efficient and
distributed clustering methods respectively. They aim to extend the
network lifetime while ensuring the coverage. S. Misra et al.
\cite{Misra05} proposed a localized algorithm which conserves energy and
%\begin{itemize}
%\item
{\indent \bf How must the phases for information exchange, decision
- and sensing be planned over time?} Our algorithm divides the time
-line into rounds. Each round contains 4 phases: Information Exchange,
+ and sensing be planned over time?} Our algorithm divides the timeline into rounds. Each round contains 4 phases: Information Exchange,
Leader Election, Decision, and Sensing.
%\item
distributed method is clearly required.
\begin{table}[ht]
-\caption{EXEC. TIME(S) VS. NUMBER OF SENSORS}
+\caption{EXECUTION TIME(S) VS. NUMBER OF SENSORS}
% title of Table
\centering
optimization problem by partitioning it in many smaller problems, one
per subregion, that can be solved more easily. In future work, we
plan to study a coverage protocol which computes all active sensor
-schedules in one time, using optimization methods such as swarms
-optimization or evolutionary algorithms.
+schedules in only one step for many rounds, using optimization methods
+such as swarms optimization or evolutionary algorithms.
% use section* for acknowledgement
%\section*{Acknowledgment}
