-\indent In the last years, there has been increasing development in wireless networking,
-Micro-Electro-Mechanical Systems (MEMS), and embedded computing technologies, which are led to construct low-cost, small-sized and low-power sensor nodes that can perform detection, computation and data communication of surrounding environment. WSN
-includes a large number of small, limited-power sensors that can
-sense, process and transmit data over a wireless communication. They
-communicate with each other by using multi-hop wireless communications, cooperate together to monitor the area of interest,
-and the measured data can be reported to a monitoring center called sink
-for analysis it~\cite{Sudip03}. There are several applications used the
-WSN including health, home, environmental, military, and industrial
-applications~\cite{Akyildiz02}. One of the major scientific research challenges in WSNs, which are addressed by a large number of literature during the last few years is to design energy efficient approches for coverage and connectivity in WSNs~\cite{conti2014mobile}.The coverage problem is one of the
-fundamental challenges in WSNs~\cite{Nayak04} that consists in monitoring efficiently and continuously
-the area of interest. The limited energy of sensors represents the main challenge in WSNs
-design~\cite{Sudip03}, where it is impossible or inconvenient to replace and/or recharge their batteries because the the area of interest nature (such
-as remote, hostile or unpractical environments) and the cost. So, it is necessary that a WSN
-deployed with high density because spatial redundancy can then be
-exploited to increase the lifetime of the network. However, turn on
-all the sensor nodes, which monitor the same region at the same time
-leads to decrease the lifetime of the network. To extend the lifetime
-of the network, the main idea is to take advantage of the overlapping
-sensing regions of some sensor nodes to save energy by turning off
-some of them during the sensing phase~\cite{Misra05}. WSNs require
-energy-efficient solutions to improve the network lifetime that is
-constrained by the limited power of each sensor node ~\cite{Akyildiz02}. In this paper, we concentrate on the area
-coverage problem, with the objective of maximizing the network
-lifetime by using an adaptive scheduling. The area of interest is
-divided into subregions and an activity scheduling for sensor nodes is
-planned for 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 scheduling scheme considers rounds, where
-a round starts with a discovery phase to exchange information between
-sensors of the subregion, in order to choose in a suitable manner a
-sensor node to carry out a coverage strategy. This coverage strategy
-involves the solving of an integer program, which provides the
-activation of the sensors for the sensing phase of the current round.
+\indent In the last years, there has been an increasing development in wireless
+networking, Micro-Electro-Mechanical Systems (MEMS), and embedded computing
+technologies, which have led to construct low-cost, small-sized, and low-power
+sensor nodes that can perform detection, computation, and data communication of
+surrounding environment. A WSN includes a large number of small, limited-power
+sensors that can sense, process, and transmit data over a wireless
+communication. They communicate with each other by using multi-hop wireless
+communications and cooperate together to monitor the area of interest, so that
+each measured data can be reported to a monitoring center called sink for
+further analysis~\cite{Sudip03}.
+
+There are several fields of application covering a wide spectrum for a WSN,
+including health, home, environmental, military, and industrial
+applications~\cite{Akyildiz02}. 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}. On the one hand an optimal
+coverage~\cite{Nayak04} is required to monitor efficiently and continuously the
+area of interest and on the other hand the energy consumption must be as low as
+possible, due to the limited energy of sensors~\cite{Sudip03} and the
+impossibility or difficulty to replace and/or recharge their batteries because
+of the area of interest nature (such as remote, hostile, or unpractical
+environments) and the cost. So, it is of great relevance for a WSN to be
+deployed with high density, because spatial redundancy can then be exploited to
+increase the lifetime of the network. However, turning on all the sensor nodes
+which monitor the same region at the same time reduces the the lifetime of the
+network. Therefore, to extend the lifetime of the network, the main idea is to
+take advantage of the overlapping sensing regions of some sensor nodes to save
+energy by turning off some of them during the sensing phase~\cite{Misra05}.
+
+In this paper we concentrate on the area coverage problem with the objective of
+maximizing the network lifetime by using an adaptive scheduling. The area of
+interest is divided into subregions and an activity scheduling for sensor nodes
+is planned for 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 scheduling scheme
+considers rounds, where a round starts with a discovery phase to exchange
+information between sensors of the subregion, in order to choose in a suitable
+manner a sensor node to carry out a coverage strategy. This coverage strategy
+involves the solving of an integer program, which provides the activation of the
+sensors for the sensing phase of the current round.
