From a2d993a3268c260445a6fcb9a5f04f9a7d30ae78 Mon Sep 17 00:00:00 2001 From: Karine Deschinkel Date: Tue, 13 Jan 2015 14:34:47 +0100 Subject: [PATCH 1/1] petits details --- LiCO_Journal.tex | 9 +++++---- 1 file changed, 5 insertions(+), 4 deletions(-) diff --git a/LiCO_Journal.tex b/LiCO_Journal.tex index fca3d13..4cabd73 100644 --- a/LiCO_Journal.tex +++ b/LiCO_Journal.tex @@ -60,7 +60,7 @@ 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 a such approach called Lifetime Coverage Optimization +this paper, we propose such an approach called Lifetime Coverage Optimization protocol (LiCO). 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. A sensor node which runs LiCO @@ -321,7 +321,7 @@ complete coverage of a convex area implies connectivity among active nodes. Tseng in~\cite{huang2005coverage}. It can be expressed as follows: a sensor is said to be perimeter covered if all the points on its perimeter are covered by at least one sensor other than itself. They proved that a network area is -$k$-covered if and only if each sensor in the network is $k$-perimeter-covered. +$k$-covered if and only if each sensor in the network is $k$-perimeter-covered (perimeter covered by at least $k$ sensors). %According to this model, we named the intersections among the sensor nodes in the sensing field as intersection points. Instead of working with the coverage area, we consider for each sensor a set of intersection points which are determined by using perimeter-coverage model. Figure~\ref{pcm2sensors}(a) shows the coverage of sensor node~$0$. On this figure, we can see that sensor~$0$ has nine neighbors and we have reported on @@ -365,7 +365,8 @@ positions. The intersection points are then visited one after another, starting from first intersection point after point~zero, and the maximum level of coverage is determined for each interval defined by two successive points. The maximum level of coverage is equal to the number of overlapping arcs. For -example, between~$5L$ and~$6L$ the maximum level of coverage is equal to $3$ +example, +between~$5L$ and~$6L$ the maximum level of coverage is equal to $3$ (the value is highlighted in yellow at the bottom of figure~\ref{expcm}), which means that at most 2~neighbors can cover the perimeter in addition to node $0$. Table~\ref{my-label} summarizes for each coverage interval the maximum level of @@ -829,7 +830,7 @@ it corresponds to the configuration producing the better results for DiLCO. The protocols are distinguished from one another by the formulation of the integer program providing the set of sensors which have to be activated in each sensing phase. DiLCO protocol tries to satisfy the coverage of a set of primary points, -whereas LiCO protocol objectif is to reach a desired level of coverage for each +whereas LiCO protocol objective is to reach a desired level of coverage for each sensor perimeter. In our experimentations, we chose a level of coverage equal to one ($l=1$). -- 2.39.5