X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/LiCO.git/blobdiff_plain/1730ca37e00cce6bd1ad7cf3cd23eb3cb397bc35..3b6e0c9402cf8ca8e7daec7f4520685de215e5df:/PeCO-EO/articleeo.tex?ds=inline diff --git a/PeCO-EO/articleeo.tex b/PeCO-EO/articleeo.tex index bb97acb..82007ff 100644 --- a/PeCO-EO/articleeo.tex +++ b/PeCO-EO/articleeo.tex @@ -15,13 +15,12 @@ \title{{\itshape Perimeter-based Coverage Optimization to Improve Lifetime \\ in Wireless Sensor Networks}} -\author{Ali Kadhum Idrees$^{a, b}$, Karine Deschinkel$^{a}$$^{\ast}$\thanks{$^\ast$Corresponding author. Email: karine.deschinkel@univ-fcomte.fr}, Michel Salomon$^{a}$ and Rapha\"el Couturier $^{a}$ -$^{a}${\em{FEMTO-ST Institute, UMR 6174 CNRS, University of Franche-Comt\'e, - Belfort, France}} -$^{b}${\em{Department of Computer Science, University of Babylon, Babylon, Iraq}} } - - - +\author{Ali Kadhum Idrees$^{a,b}$, Karine Deschinkel$^{a}$$^{\ast}$\thanks{$^\ast$Corresponding author. Email: karine.deschinkel@univ-fcomte.fr}, Michel Salomon$^{a}$ and Rapha\"el Couturier $^{a}$ + $^{a}${\em{FEMTO-ST Institute, UMR 6174 CNRS, \\ + University Bourgogne Franche-Comt\'e (UBFC), Belfort, France}} \\ + $^{b}${\em{Department of Computer Science, University of Babylon, Babylon, Iraq}} +} + \maketitle \begin{abstract} @@ -309,7 +308,7 @@ above is thus given by the sixth line of the table. \begin{figure*}[t!] \centering -\includegraphics[width=0.95\linewidth]{figure2.eps} +\includegraphics[width=0.9\linewidth]{figure2.eps} \caption{Maximum coverage levels for perimeter of sensor node $0$.} \label{figure2} \end{figure*} @@ -392,7 +391,7 @@ of the application. \begin{figure}[t!] \centering -\includegraphics[width=85mm]{figure4.eps} +\includegraphics[width=80mm]{figure4.eps} \caption{PeCO protocol.} \label{figure4} \end{figure} @@ -668,7 +667,7 @@ coverage task. This value corresponds to the energy needed by the sensing phase, obtained by multiplying the energy consumed in the active state (9.72 mW) with the time in seconds for one period (3600 seconds), and adding the energy for the pre-sensing phases. According to the interval of initial energy, a sensor may -be active during at most 20 periods. +be active during at most 20 periods. Here information exchange is executed every hour but the length of the sensing period could be reduced and adapted dynamically. On the one hand a small sensing period would allow to be more reliable but would have higher communication costs. On the other hand the choice of a long duration may cause problems in case of nodes failure during the sensing period. The values of $\alpha^j_i$ and $\beta^j_i$ have been chosen to ensure a good network coverage and a longer WSN lifetime. Higher priority is given to the @@ -775,7 +774,13 @@ based on the energy model proposed in \citep{ChinhVu}. The modeling language for Mathematical Programming (AMPL)~\citep{AMPL} is used to generate the integer program instance in a standard format, which is then read and solved by the optimization solver GLPK (GNU linear Programming Kit -available in the public domain) \citep{glpk} through a Branch-and-Bound method. +available in the public domain) \citep{glpk} through a Branch-and-Bound method. +Obviously executing GLPK in practice on a sensor node is usually untractable due to +the huge memory use. Fortunately, to solve the optimization problem we could use +commercial solvers like CPLEX which are less memory consuming and more efficient, or +implement a lightweight heuristic. For example, for a WSN of 200 sensor nodes, a leader +node has to deal with constraints induced by about 12 sensor nodes. In that case, to solve the optimization problem a +memory consumption of more than 1 MB can be observed with GLPK, whereas with CPLEX less than 300 kB would be needed. % No discussion about the execution of GLPK on a sensor ? @@ -789,7 +794,9 @@ protocol~\citep{Idrees2}, is an improved version of a research work we presented in~\citep{idrees2014coverage}. Let us notice that PeCO and DiLCO protocols are based on the same framework. In particular, the choice for the simulations of a partitioning in 16~subregions was made because it corresponds to the -configuration producing the best results for DiLCO. The protocols are +configuration producing the best results for DiLCO. Of course, this number of subregions sould be adapted according to the size of the area of interest and the number of sensors. + + 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, @@ -974,7 +981,7 @@ sensor-testbed to evaluate it in real world applications. \subsection{Acknowledgements} -The authors are deeply grateful to the anonymous reviewers for their constructive advice, which improved the technical quality of the paper. As a Ph.D. student, Ali Kadhum IDREES would like to gratefully acknowledge the University of Babylon - IRAQ for financial support and Campus France for the received support. This work is also partially funded by the Labex ACTION program (contract ANR-11-LABX-01-01). +The authors are deeply grateful to the anonymous reviewers for their constructive advice, which improved the technical quality of the paper. As a Ph.D. student, Ali Kadhum IDREES would like to gratefully acknowledge the University of Babylon - Iraq for financial support and Campus France for the received support. This work is also partially funded by the Labex ACTION program (contract ANR-11-LABX-01-01). \bibliographystyle{gENO} \bibliography{biblio} %articleeo