\keywords{Wireless Sensor Networks, Area Coverage, Network lifetime,
Optimization, Scheduling.}
-\abstract{One of the fundamental challenges in Wireless Sensor Networks (WSNs) is the
-coverage preservation and the extension of the network lifetime continuously and
-effectively when monitoring a certain area (or region) of interest. In this
-paper, a Distributed Lifetime Coverage Optimization protocol (DiLCO) to maintain
-the coverage and to improve the lifetime in wireless sensor networks is
-proposed. The area of interest is first divided into subregions using a
-divide-and-conquer method and then the DiLCO protocol is distributed on the
-sensor nodes in each subregion. The DiLCO combines two efficient techniques:
-leader election for each subregion, followed by an optimization-based activity scheduling for each subregion. The proposed DiLCO works
-into periods during which a small number of nodes, remaining active for sensing,
-is selected to ensure coverage so as to maximize the lifetime of wireless sensor
-network. Each period consists of 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. Compared with
-some existing protocols, simulation results show that the proposed protocol can
-prolong the network lifetime and improve the coverage performance effectively.}
+\abstract{ One of the main research challenges faced in Wireless Sensor Networks
+ (WSNs) is to preserve continuously and effectively the coverage of an area (or
+ region) of interest to be monitored, while simultaneously preventing as much
+ as possible a network failure due to battery-depleted nodes. In this paper we
+ propose a protocol, called Distributed Lifetime Coverage Optimization protocol
+ (DiLCO), which maintains the coverage and improves the lifetime of a wireless
+ sensor network. As a first step we partition the area of interest into
+ subregions using a classical divide-and-conquer method. Our DiLCO protocol is
+ then distributed on the sensor nodes in each subregion in a second step. To
+ fulfill our objective, the proposed protocol combines two effective
+ techniques: a leader election in each subregion, followed by an
+ optimization-based node activity scheduling performed by each elected leader.
+ This two-step process takes place periodically, in order to choose a small set
+ of nodes remaining active for sensing during a time slot. Each set is built
+ to ensure coverage at a low energy cost, allowing to optimize the network
+ lifetime. More precisely, a period consists of four phases: (i)~Information
+ Exchange, (ii)~Leader Election, (iii)~Decision, and (iv)~Sensing. The
+ decision process, which result in an activity scheduling vector, is carried
+ out by a leader node through the solving of an integer program. In comparison
+ with some other protocols, the simulations done using the discrete event
+ simulator OMNeT++ show that our approach is able to increase the WSN lifetime
+ and provides improved coverage performance. }
\onecolumn \maketitle \normalsize \vfill
\section{\uppercase{Introduction}}
\label{sec:introduction}
\noindent
-Energy efficiency is very important issue in WSNs since sensors are powered by batteries. Therefore, reducing energy consumption and extending network lifetime are the main challenges in the design of WSNs. One of the major scientific research challenges in WSNs, which has been addressed by a large amount of literature during the last few years, is the design of energy efficient approaches for coverage and connectivity~\cite{conti2014mobile}.
-Coverage reflects how well a sensor field is monitored. The most discussed coverage problems in literature can be classified
-into three types \cite{li2013survey}: area coverage (where every
-point inside an area is to be monitored), target coverage (where the main objective is to cover only a finite number of discrete
-points called targets), and barrier coverage (the problem of preventing an intruder from entering a region of interest is referred to as the barrier coverage).
- It is required to monitor the area of interest efficiently~\cite{Nayak04}, but in the same time the power consumption should be minimized. Sensor nodes runs on batteries with limited capacities~\cite{Sudip03} and it is impossible, difficult or expensive to recharge and/or replace batteries in remote, hostile, or unpractical environments. Therefore, it is desired that the WSNs are deployed with high densities so as to exploit the overlapping sensing regions of some sensor nodes to save energy by turning off some of them during the sensing phase to prolong the network lifetime.
-
-In this paper we concentrate on the area coverage problem with the objective of
-maximizing the network lifetime by using DiLCO protocol to maintain the coverage and to improve the lifetime in WSNs. The area of interest is divided into subregions using divide-and-conquer method and an activity scheduling for sensor nodes is planned by the elected leader in each subregion. In fact, the nodes in a subregion can be seen as a cluster where each node sends sensing data to the cluster head or the sink node. Furthermore, the activities in a subregion/cluster can continue even if another cluster stops due to too many node failures. Our DiLCO protocol considers periods, where a period starts with a discovery phase to exchange information between sensors of the subregion, in order to choose in a suitable manner a sensor node (the leader) to carry out the coverage strategy. Our DiLCO protocol involves solving an integer program, which provides the activation of the sensors for the sensing phase of the current period.
-
-The remainder of the paper is organized as follows. The next section reviews the related work in the field. Section~\ref{sec:The DiLCO Protocol Description} is devoted to the DiLCO protocol Description. Section~\ref{cp} gives the coverage model
-formulation which is used to schedule the activation of sensors.
-Section~\ref{sec:Simulation Results and Analysis} shows the simulation results. Finally, we give concluding remarks and some suggestions for
-future works in Section~\ref{sec:Conclusion and Future Works}.
+Energy efficiency is a crucial issue in wireless sensor networks since sensor
+nodes drain their energy from batteries. In fact, strong constraints on energy
+consumption, in order to maximize the network lifetime, represent the major
+difficulty when designing WSNs. As a consequence, one of the scientific research
+challenges in WSNs, which has been addressed by a large amount of literature
+during the last few years, is the design of energy efficient approaches for
+coverage and connectivity~\cite{conti2014mobile}. Coverage reflects how well a
+sensor field is monitored. The most discussed coverage problems in literature
+can be classified into three types \cite{li2013survey}: area coverage (where
+every point inside an area is to be monitored), target coverage (where the main
+objective is to cover only a finite number of discrete points called targets),
+and barrier coverage (to prevent intruders from entering into the region of
+interest). On the one hand we want to monitor the area of interest in the most
+efficient way~\cite{Nayak04}. On the other hand we want to use as less energy as
+possible. % TO BE CONTINUED
+Sensor nodes runs on batteries with limited capacities~\cite{Sudip03}
+and it is impossible, difficult or expensive to recharge and/or replace
+batteries in remote, hostile, or unpractical environments. Therefore, it is
+desired that the WSNs are deployed with high densities so as to exploit the
+overlapping sensing regions of some sensor nodes to save energy by turning off
+some of them during the sensing phase to prolong the network lifetime.
+
+In this paper we concentrate on the area coverage problem with the objective of
+maximizing the network lifetime by using DiLCO protocol to maintain the coverage
+and to improve the lifetime in WSNs. The area of interest is divided into
+subregions using divide-and-conquer method and an activity scheduling for sensor
+nodes is planned by the elected leader in each subregion. In fact, the nodes in
+a subregion can be seen as a cluster where each node sends sensing data to the
+cluster head or the sink node. Furthermore, the activities in a
+subregion/cluster can continue even if another cluster stops due to too many
+node failures. Our DiLCO protocol considers periods, where a period starts with
+a discovery phase to exchange information between sensors of the subregion, in
+order to choose in a suitable manner a sensor node (the leader) to carry out the
+coverage strategy. Our DiLCO protocol involves solving an integer program,
+which provides the activation of the sensors for the sensing phase of the
+current period.
+
+The remainder of the paper continues with Section~\ref{sec:Literature Review}
+where a review of some related works is presented. The next section describes
+the DiLCO protocol, followed in Section~\ref{cp} by the coverage model
+formulation which is used to schedule the activation of
+sensors. Section~\ref{sec:Simulation Results and Analysis} shows the simulation
+results. The paper ends with conclusions and some suggestions for futher work in
+Section~\ref{sec:Conclusion and Future Works}.
\section{\uppercase{Literature Review}}
\label{sec:Literature Review}
