\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}
Every couple of intersection points is placed on the angular interval $[0,2\pi]$
in a counterclockwise manner, leading to a partitioning of the interval.
Figure~\ref{pcm2sensors}(a) illustrates the arcs for the nine neighbors of
-sensor $0$ and Figure~\ref{expcm} gives the position of the corresponding arcs
+sensor $0$ and Figure~\ref{expcm} gives the position of the corresponding arcs
in the interval $[0,2\pi]$. More precisely, we can see that the points are
ordered according to the measures of the angles defined by their respective
positions. The intersection points are then visited one after another, starting
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
