X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/ThesisAli.git/blobdiff_plain/c5833cac353b334ae2450046541cb61c6b5b54e3..e17c9931e4c1607fff951e7ac261dcc949249ead:/CONCLUSION.tex

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 In this dissertation, we have concentrated on proposing a distributed optimization protocols so as to prolong the lifetime of wireless sensor networks. We have addressed the problem of the area coverage and the lifetime optimization in wireless sensor networks, where the ultimate goal is the coverage preservation and the extension of the network lifetime continuously and effectively when monitoring a certain area (or region) of interest. 
 
-\section*{Perspectives}
+The first part of the dissertation has presented the scientific background including WSNs, brief survey of related works, and evaluation tools as well as optimization solvers.  
 
+In chapter 1, We have began with a general overview on wireless sensor networks. We have described various concepts, mechanisms, types, applications, and challenges in WSNs. We have presented several energy-efficient techniques so as to improve the network lifetime of WSNs. The coverage problem, the network lifetime, and the energy consumption modeling in WSNs have explained. A brief survey about coverage algorithms in literature is achieved in chapter 2.
+We have classified those works into centralized and distributed algorithms. We have given a brief comparison of the main characteristics of each approach. This part finally included in chapter 3, a comparative study of different evaluation tools dedicated to WSNs. In addition, we have illustrated a various commercial and free optimization solvers considering the main features of each one.
 
+In the second part of the dissertation, We have designed a new three different optimization protocols, which schedules nodes’ activities (wake up and sleep stages) with the objective of maintaining a good coverage ratio while maximizing the network lifetime in WSNs. This part proposes a two-step approaches. Firstly, the field of sensing is divided into smaller subregions using the concept of divide-and-conquer method. Secondly, one of the proposed optimization protocols is applied in each subregion in a distributed parallel way to optimize the coverage and lifetime performances. The proposed protocols combine two efficient mechanisms: network leader election and sensor activity scheduling, where the challenges include how to select the most efficient leader in each subregion and the best
+representative active nodes that will optimize the network lifetime while taking the responsibility of covering the corresponding subregion.
 
 
 
+In chapter 4, 
+ 
 
+ 
 
 
 
 
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+
+\section*{Perspectives}
+
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