+\noindent In this section, we summarize some related works regarding the
+coverage problem and distinguish our DiLCO protocol from the works presented in
+the literature.
+
+The most discussed coverage problems in literature can be classified into three
+types \cite{li2013survey}: area coverage \cite{Misra} where every point inside
+an area is to be monitored, target coverage \cite{yang2014novel} where the main
+objective is to cover only a finite number of discrete points called targets,
+and barrier coverage \cite{Kumar:2005}\cite{kim2013maximum} to prevent intruders
+from entering into the region of interest. In \cite{Deng2012} authors transform
+the area coverage problem to the target coverage problem taking into account the
+intersection points among disks of sensors nodes or between disk of sensor nodes
+and boundaries. {\it In DiLCO protocol, the area coverage, i.e. the coverage of
+ every point in the sensing region, is transformed to the coverage of a
+ fraction of points called primary points. }
+
+The major approach to extend network lifetime while preserving coverage is to
+divide/organize the sensors into a suitable number of set covers (disjoint or
+non-disjoint), where each set completely covers a region of interest, and to
+activate these set covers successively. The network activity can be planned in
+advance and scheduled for the entire network lifetime or organized in periods,
+and the set of active sensor nodes is decided at the beginning of each period
+\cite{ling2009energy}. Active node selection is determined based on the problem
+requirements (e.g. area monitoring, connectivity, power efficiency). For
+instance, Jaggi et al. \cite{jaggi2006} address the problem of maximizing
+network lifetime by dividing sensors into the maximum number of disjoint subsets
+so that each subset can ensure both coverage and connectivity. A greedy
+algorithm is applied once to solve this problem and the computed sets are
+activated in succession to achieve the desired network lifetime. Vu
+\cite{chin2007}, Padmatvathy et al. \cite{pc10}, propose algorithms working in a
+periodic fashion where a cover set is computed at the beginning of each period.
+{\it Motivated by these works, DiLCO protocol works in periods, where each
+ period contains a preliminary phase for information exchange and decisions,
+ followed by a sensing phase where one cover set is in charge of the sensing
+ task.}
+
+Various approaches, including centralized, or distributed algorithms, have been
+proposed to extend the network lifetime. In distributed
+algorithms~\cite{yangnovel,ChinhVu,qu2013distributed}, information is
+disseminated throughout the network and sensors decide cooperatively by
+communicating with their neighbors which of them will remain in sleep mode for a
+certain period of time. The centralized
+algorithms~\cite{cardei2005improving,zorbas2010solving,pujari2011high} always
+provide nearly or close to optimal solution since the algorithm has global view
+of the whole network. But such a method has the disadvantage of requiring high
+communication costs, since the node (located at the base station) making the
+decision needs information from all the sensor nodes in the area and the amount
+of information can be huge. {\it In order to be suitable for large-scale
+ network, in the DiLCO protocol, the area coverage is divided into several
+ smaller subregions, and in each one, a node called the leader is in charge for
+ selecting the active sensors for the current period.}
+
+% MODIF - BEGIN
+ Our approach to select the leader node in a subregion is quite
+ different from cluster head selection methods used in LEACH
+ \cite{DBLP:conf/hicss/HeinzelmanCB00} or its variants
+ \cite{ijcses11}. Contrary to LEACH, the division of the area of interest is
+ supposed to be performed before the leader election. Moreover, we assume that
+ the sensors are deployed almost uniformly and with high density over the area
+ of interest, so that the division is fixed and regular. As in LEACH, our
+ protocol works in round fashion. In each round, during the pre-sensing phase,
+ nodes make autonomous decisions. In LEACH, each sensor elects itself to be a
+ cluster head, and each non-cluster head will determine its cluster for the
+ round. In our protocol, nodes in the same subregion select their leader. In
+ both protocols, the amount of remaining energy in each node is taken into
+ account to promote the nodes that have the most energy to become leader.
+ Contrary to the LEACH protocol where all sensors will be active during the
+ sensing-phase, our protocol allows to deactivate a subset of sensors through
+ an optimization process which significantly reduces the energy consumption.
+% MODIF - END
+
+A large variety of coverage scheduling algorithms has been developed. Many of
+the existing algorithms, dealing with the maximization of the number of cover
+sets, are heuristics. These heuristics involve the construction of a cover set
+by including in priority the sensor nodes which cover critical targets, that is
+to say targets that are covered by the smallest number of sensors
+\cite{berman04,zorbas2010solving}. Other approaches are based on mathematical
+programming formulations~\cite{cardei2005energy,5714480,pujari2011high,Yang2014}
+and dedicated techniques (solving with a branch-and-bound algorithms available
+in optimization solver). The problem is formulated as an optimization problem
+(maximization of the lifetime or number of cover sets) under target coverage and
+energy constraints. Column generation techniques, well-known and widely
+practiced techniques for solving linear programs with too many variables, have
+also been
+used~\cite{castano2013column,rossi2012exact,deschinkel2012column}. {\it In DiLCO
+ protocol, each leader, in each subregion, solves an integer program with a
+ double objective consisting in minimizing the overcoverage and limiting the
+ undercoverage. This program is inspired from the work of \cite{pedraza2006}
+ where the objective is to maximize the number of cover sets.}
+
+\section{\uppercase{Description of the DiLCO protocol}}
