X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/ThesisAli.git/blobdiff_plain/ea03ef6a15b12c2b2cd5cdee7f72ca18a520c387..28fe5f530e0e9ae044a4463fd7eb3646cc5dd04c:/CHAPITRE_06.tex?ds=inline diff --git a/CHAPITRE_06.tex b/CHAPITRE_06.tex index 31e696c..bd0cdf8 100644 --- a/CHAPITRE_06.tex +++ b/CHAPITRE_06.tex @@ -7,29 +7,6 @@ \chapter{Perimeter-based Coverage Optimization to Improve Lifetime in Wireless Sensor Networks} \label{ch6} -\iffalse - -\section{Summary} -\label{ch6:sec:01} - -The most important problem in a Wireless Sensor Network (WSN) is to optimize the -use of its limited energy provision so that it can fulfill its monitoring task -as long as possible. Among known available approaches that can be used to -improve power management, lifetime coverage optimization provides activity -scheduling which ensures sensing coverage while minimizing the energy cost. In -this paper, we propose such an approach called Perimeter-based Coverage Optimization -protocol (PeCO). It is a hybrid of centralized and distributed methods: the -region of interest is first subdivided into subregions and our protocol is then -distributed among sensor nodes in each subregion. -The novelty of our approach lies essentially in the formulation of a new -mathematical optimization model based on the perimeter coverage level to schedule -sensors' activities. Extensive simulation experiments have been performed using -OMNeT++, the discrete event simulator, to demonstrate that PeCO can -offer longer lifetime coverage for WSNs in comparison with some other protocols. - - -\fi - \section{Introduction} \label{ch6:sec:01} @@ -412,7 +389,7 @@ be active during at most 20 periods. The values of $\alpha^j_i$ and $\beta^j_i$ have been chosen to ensure a good network coverage and a longer WSN lifetime. We have given a higher priority to -the undercoverage (by setting the $\alpha^j_i$ with a larger value than +the undercoverage (by setting the $\alpha^j_i$ with a larger value than $\beta^j_i$) so as to prevent the non-coverage for the interval~$i$ of the sensor~$j$. On the other hand, we have assigned to $\beta^j_i$ a value which is slightly lower so as to minimize the number of active sensor nodes which contribute