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[ThesisAli.git] / CHAPITRE_05.tex

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 \chapter{Multiround Distributed Lifetime Coverage Optimization Protocol in Wireless Sensor Networks}
 \label{ch5}
 
 \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
-Optimization  protocol (MuDiLCO)  is proposed  to maintain  the coverage  and to improve the lifetime in wireless sensor  networks. The area of interest is first
-divided  into subregions and  then the  MuDiLCO protocol  is distributed  on the sensor nodes in each subregion. The proposed MuDiLCO protocol works in periods
-during which sets of sensor nodes are scheduled to remain active for a number of rounds  during the  sensing phase,  to ensure coverage  so as  to maximize the
-lifetime of  WSN. The decision process is  carried out by a  leader node, which solves an  integer program to  produce the best  representative sets to  be used
-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}
 
 \section{Introduction}
 \label{ch5:sec:01}


@@ -268,8 +255,7 @@ large compared to $W_{\theta}$.
 \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++
 \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
-25 runs.
+\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 25 runs.

 %Based on the results of our proposed work in~\cite{idrees2014coverage}, we found as the region of interest are divided into larger subregions as the network lifetime increased. In this simulation, the network are divided into 16 subregions. 
 We  performed  simulations for  five  different  densities  varying from  50  to
 250~nodes deployed  over  a  $50 \times  25~m^2  $  sensing field.  More
 %Based on the results of our proposed work in~\cite{idrees2014coverage}, we found as the region of interest are divided into larger subregions as the network lifetime increased. In this simulation, the network are divided into 16 subregions. 
 We  performed  simulations for  five  different  densities  varying from  50  to
 250~nodes deployed  over  a  $50 \times  25~m^2  $  sensing field.  More