X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/LiCO.git/blobdiff_plain/74ea4422621d70b313f60f78c80a29abe506d6b4..13e36b88aa716dccc5034ac947365d94388d71ae:/PeCO-EO/articleeo.tex?ds=inline diff --git a/PeCO-EO/articleeo.tex b/PeCO-EO/articleeo.tex index 1dbc9e0..226726a 100644 --- a/PeCO-EO/articleeo.tex +++ b/PeCO-EO/articleeo.tex @@ -197,6 +197,15 @@ used~\citep{castano2013column,doi:10.1080/0305215X.2012.687732,deschinkel2012col +The authors in \citep{Idrees2} propose a Distributed Lifetime Coverage Optimization (DiLCO) protocol, maintains the coverage and improves the lifetime in WSNs. It is an improved version +of a research work they presented in~\citep{idrees2014coverage}. First, they partition the area of interest into subregions using a divide-and-conquer method. DiLCO protocol is then distributed on the sensor nodes in each subregion in a second step. DiLCO protocol combines two techniques: a leader election in each subregion, followed by an optimization-based node activity scheduling performed by each elected leader. The proposed DiLCO protocol is a periodic protocol where each period is decomposed into 4 phases: information exchange, leader election, decision, and sensing. The simulations show that DiLCO is able to increase the WSN lifetime and provides improved coverage performance. {\it In the PeCO + protocol, We have proposed a new mathematical optimization model. Instead of trying to +cover a set of specified points/targets as in DiLCO protocol, we formulate an integer program based +on perimeter coverage of each sensor. The model involves integer variables to capture the deviations between the actual level of coverage and the required level. The idea is that an optimal scheduling will be obtained by minimizing a weighted sum of these deviations.} + + + + \section{ The P{\scshape e}CO Protocol Description} \label{sec:The PeCO Protocol Description} @@ -823,6 +832,29 @@ not ineffective for the smallest network sizes. \end{figure} +\subsubsection{\bf Impact of $\alpha$ and $\beta$ on PeCO's performance} +Table~\ref{my-labelx} explains all possible network lifetime result of the relation between the different values of $\alpha$ and $\beta$, and for a network size equal to 200 sensor nodes. As can be seen in Table~\ref{my-labelx}, it is obvious and clear that when $\alpha$ decreased and $\beta$ increased by any step, the network lifetime for $Lifetime_{50}$ increased and the $Lifetime_{95}$ decreased. Therefore, selecting the values of $\alpha$ and $\beta$ depend on the application type used in the sensor nework. In PeCO protocol, $\alpha$ and $\beta$ are chosen based on the largest value of network lifetime for $Lifetime_{95}$. + +\begin{table}[h] +\centering +\caption{The impact of $\alpha$ and $\beta$ on PeCO's performance} +\label{my-labelx} +\begin{tabular}{|c|c|c|c|} +\hline +$\alpha$ & $\beta$ & $Lifetime_{50}$ & $Lifetime_{95}$ \\ \hline +0.0 & 1.0 & 151 & 0 \\ \hline +0.1 & 0.9 & 145 & 0 \\ \hline +0.2 & 0.8 & 140 & 0 \\ \hline +0.3 & 0.7 & 134 & 0 \\ \hline +0.4 & 0.6 & 125 & 0 \\ \hline +0.5 & 0.5 & 118 & 30 \\ \hline +0.6 & 0.4 & 94 & 57 \\ \hline +0.7 & 0.3 & 97 & 49 \\ \hline +0.8 & 0.2 & 90 & 52 \\ \hline +0.9 & 0.1 & 77 & 50 \\ \hline +1.0 & 0.0 & 60 & 44 \\ \hline +\end{tabular} +\end{table} \section{Conclusion and Future Works} @@ -838,7 +870,7 @@ is based on the resolution of an integer program to select the subset of sensors operating in active status for each period. Our work is original in so far as it proposes for the first time an integer program scheduling the activation of sensors based on their perimeter coverage level, instead of using a set of -targets/points to be covered. +targets/points to be covered. We have carried out several simulations to evaluate the proposed protocol. The @@ -856,7 +888,7 @@ Finally, it would be interesting to implement our protocol using a sensor-testbed to evaluate it in real world applications. \bibliographystyle{gENO} -\bibliography{biblio} +\bibliography{articleeo} \end{document}