\chapter{Multiround Distributed Lifetime Coverage Optimization Protocol in Wireless Sensor Networks}
\label{ch5}
+\iffalse
+
\section{Summary}
\label{ch5:sec:01}
Coverage and lifetime are two paramount problems in Wireless Sensor Networks (WSNs). In this paper, a method called Multiround Distributed Lifetime Coverage
during the rounds of the sensing phase. Compared with some existing protocols, simulation results based on multiple criteria (energy consumption, coverage
ratio, and so on) show that the proposed protocol can prolong efficiently the network lifetime and improve the coverage performance.
+\fi
+
+\section{Introduction}
+\label{ch5:sec:01}
+
+\indent The fast developments of low-cost sensor devices and wireless
+communications have allowed the emergence of WSNs. 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{ref222}. There are several fields of application
+covering a wide spectrum for a WSN, including health, home, environmental,
+military, and industrial applications~\cite{ref19}.
+
+On the one hand sensor nodes run on batteries with limited capacities, and it is
+often costly or simply impossible to replace and/or recharge batteries,
+especially in remote and hostile environments. Obviously, to achieve a long life
+of the network it is important to conserve battery power. Therefore, lifetime
+optimization is one of the most critical issues in wireless sensor networks. On
+the other hand we must guarantee coverage over the area of interest. To fulfill
+these two objectives, the main idea is to take advantage of overlapping sensing
+regions to turn-off redundant sensor nodes and thus save energy. In this paper,
+we concentrate on the area coverage problem, with the objective of maximizing
+the network lifetime by using an optimized multiround scheduling.
+
+We study the problem of designing an energy-efficient optimization algorithm that divides the sensor nodes in a WSN into multiple cover sets such that the area of interest is monitored as long as possible. Providing multiple cover sets can be used to improve the energy efficiency of WSNs. Therefore, in order to increase the longevity of the WSN and conserve the energy, it can be useful to provide multiple cover sets in one time after that schedule them for multiple rounds, so that the battery life of a sensor is not wasted due to the repeated execution of the coverage optimization algorithm, as well as the information exchange and leader election.
+
+The MuDiLCO protocol (for Multiround Distributed Lifetime Coverage Optimization protocol) presented in this chapter is an extension of the approach introduced in chapter 4. Simulation results have shown that it was more interesting to divide the area into several subregions, given the computation complexity. Compared to our protocol in chapter 4, in this one we study the possibility of dividing the sensing phase into multiple rounds. In fact, in this chapter we make a multiround optimization while it was a single round optimization in our protocol in chapter 4.
+
+
+The remainder of the chapter continues with section \ref{ch5:sec:02} where a detail of MuDiLCO Protocol is presented. The next section describes the Primary Points based Multiround Coverage Problem formulation which is used to schedule the activation of sensors in T cover sets. Section \ref{ch5:sec:04} shows the simulation
+results. The chapter ends with a conclusion and some suggestions for further work.
+
+
+
+
+
\section{MuDiLCO Protocol Description}
\label{ch5:sec:02}
\noindent In this section, we introduce the MuDiLCO protocol which is distributed on each subregion in the area of interest. It is based on two energy-efficient
-\subsection{Primary Points based Multiround Coverage Problem Formulation}
-%\label{ch5:sec:02:02}
+\section{Primary Points based Multiround Coverage Problem Formulation}
+\label{ch5:sec:03}
+
According to our algorithm~\ref{alg:MuDiLCO}, the integer program is based on the model
proposed by \cite{ref156} with some modifications, where the objective is
\section{Experimental Study and Analysis}
-\label{ch5:sec:03}
+\label{ch5:sec:04}
\subsection{Simulation Setup}
-\label{ch5:sec:03:01}
+\label{ch5:sec:04:01}
We conducted a series of simulations to evaluate the efficiency and the
relevance of our approach, using the discrete event simulator OMNeT++
\cite{ref158}. The simulation parameters are summarized in Table~\ref{table3}. Each experiment for a network is run over 25~different random topologies and the results presented hereafter are the average of these
%The initial energy of each node is randomly set in the interval $[500;700]$. A sensor node will not participate in the next round if its remaining energy is less than $E_{R}=36~\mbox{Joules}$, the minimum energy needed for the node to stay alive during one round. This value has been computed by multiplying the energy consumed in active state (9.72 mW) by the time in second for one round (3600 seconds). According to the interval of initial energy, a sensor may be alive during at most 20 rounds.
\subsection{Metrics}
-\label{ch5:sec:03:02}
+\label{ch5:sec:04:02}
To evaluate our approach we consider the following performance metrics:
\begin{enumerate}[i]
\subsection{Results Analysis and Comparison }
-\label{ch5:sec:03:02}
+\label{ch5:sec:04:02}
\begin{enumerate}[(i)]
\section{Conclusion}
-\label{ch5:sec:04}
+\label{ch5:sec:05}
We have addressed the problem of the coverage and of the lifetime optimization in wireless sensor networks. This is a key issue as sensor nodes have limited resources in terms of memory, energy, and computational power. To cope with this problem, the field of sensing is divided into smaller subregions using the concept of divide-and-conquer method, and then we propose a protocol which optimizes coverage and lifetime performances in each subregion. Our protocol,
called MuDiLCO (Multiround Distributed Lifetime Coverage Optimization) combines two efficient techniques: network leader election and sensor activity scheduling.
