X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/LiCO.git/blobdiff_plain/32b3267d56158c2c6b227fe08ec1b280fdde3606..8672f2758b38ef0ee17391e8ae39be587be825c3:/PeCO-EO/articleeo.tex~?ds=sidebyside diff --git a/PeCO-EO/articleeo.tex~ b/PeCO-EO/articleeo.tex~ index 5ba7f55..4faafaa 100644 --- a/PeCO-EO/articleeo.tex~ +++ b/PeCO-EO/articleeo.tex~ @@ -507,7 +507,7 @@ in the current period. Each sensor node determines its position and its subregion using an embedded GPS or a location discovery algorithm. After that, all the sensors collect position coordinates, remaining energy, sensor node ID, and the number of their one-hop live neighbors during the information exchange. -\textcolor{blue}{Both INFO packet and ActiveSleep packet contain two parts: header and data payload. The sensor ID is included in the header, where the header size is 8 bits. The data part includes position coordinates (64 bits), remaining energy (32 bits), and the number of one-hop live neighbors (8 bits). Therefore the size of the INFO packet is 112 bits. The ActiveSleep packet is 16 bits size, 8 bits for the header and 8 bits for data part that includes only sensor status (0 or 1).} +\textcolor{green}{Both INFO packet and ActiveSleep packet contain two parts: header and data payload. The sensor ID is included in the header, where the header size is 8 bits. The data part includes position coordinates (64 bits), remaining energy (32 bits), and the number of one-hop live neighbors (8 bits). Therefore the size of the INFO packet is 112 bits. The ActiveSleep packet is 16 bits size, 8 bits for the header and 8 bits for data part that includes only sensor status (0 or 1).} The sensors inside a same region cooperate to elect a leader. The selection criteria for the leader are (in order of priority): \begin{enumerate} @@ -719,8 +719,8 @@ approach. sensing period~$p$, $R$ is the number of subregions, and $|J|$ is the number of sensors in the network. -\item {\bf \textcolor{blue}{Energy Saving Ratio (ESR)}}: -\textcolor{blue}{this metric, which shows the ability of a protocol to save energy, is defined by: +\item {\bf \textcolor{green}{Energy Saving Ratio (ESR)}}: +\textcolor{green}{this metric, which shows the ability of a protocol to save energy, is defined by: \begin{equation*} \scriptsize \mbox{ESR}(\%) = \frac{\mbox{Number of alive sensors during this round}} @@ -853,26 +853,20 @@ keeping a greater coverage ratio as shown in Figure \ref{figure5}. \label{figure6} \end{figure} -\subsubsection{\textcolor{blue}{Energy Saving Ratio (ESR)}} - -%\textcolor{blue}{In this experiment, we study the energy saving ratio, see Figure~\ref{fig5}, for 200 deployed nodes. -%The larger the ratio is, the more redundant sensor nodes are switched off, and consequently the longer the network may liv%e. } - -\textcolor{blue}{The simulation results show that our protocol PeCO allows to - efficiently save energy by turning off some sensors during the sensing phase. - As shown in Figure~\ref{fig5}, GAF provides better energy saving than PeCO for - the first fifty rounds, because GAF balances the energy consumption among - sensor nodes inside each small fixed grid and thus permits to extend the life of - sensors in each grid fairly but in the same time turn on large number of - sensors during sensing that lead later to quickly deplete sensor's batteries - together. After that GAF provide less energy saving compared with other - approaches because of the large number of dead nodes. DESK algorithm shows less - energy saving compared with other approaches due to activate a large number of - sensors during the sensing. DiLCO protocol provides less energy saving ratio - compared with PeCO because it generally activate a larger number of sensor - nodes during sensing. Note that again as the number of rounds increases PeCO - becomes the most performing one, since it consumes less energy compared with - other approaches.} +\subsubsection{\textcolor{green}{Energy Saving Ratio}} + + +\textcolor{green}{The simulation results show that our protocol PeCO saves + efficiently energy by turning off some sensors during the sensing phase. As + shown in Figure~\ref{fig5}, GAF provides better energy saving than PeCO for + the first fifty rounds. Indeed GAF balances the energy consumption among + sensor nodes inside each small fixed grid and thus permits to extend the life + of sensors in each grid fairly. However, at the same time it turns on a large + number of sensors and that leads later to quickly deplete sensor's batteries. + DESK algorithm shows less energy saving compared with other approaches. In + comparison with PeCO, DiLCO protocol usually provides lower energy saving + ratios. Moreover, it can be noticed that after round fifty, PeCO protocol + exhibits the slowest decrease among all the considered protocols.} \begin{figure}[h!] %\centering @@ -881,9 +875,7 @@ keeping a greater coverage ratio as shown in Figure \ref{figure5}. \includegraphics[scale=0.5]{ESR.eps} %\\~ ~ ~(a) \caption{Energy Saving Ratio for 200 deployed nodes} \label{fig5} -\end{figure} - - +\end{figure} \subsubsection{Energy Consumption} @@ -940,14 +932,12 @@ for different coverage ratios. We denote by Protocol/70, Protocol/80, Protocol/85, Protocol/90, and Protocol/95 the amount of time during which the network can satisfy an area coverage greater than $70\%$, $80\%$, $85\%$, $90\%$, and $95\%$ respectively, where the term Protocol refers to DiLCO or -PeCO. \textcolor{blue}{Indeed there are applications that do not require a 100\% coverage of the +PeCO. \textcolor{green}{Indeed there are applications that do not require a 100\% coverage of the area to be monitored. For example, forest fire application might require complete coverage in summer seasons while only require 80$\%$ of the area to be covered in rainy seasons~\citep{li2011transforming}. As another example, birds habit study requires only 70$\%$-coverage at nighttime when the birds are sleeping while requires 100$\%$-coverage at daytime when the birds are active~\citep{1279193}. -%Mudflows monitoring applications may require part of the area to be covered in sunny days. Thus, to extend network lifetime, the coverage quality can be decreased if it is acceptable~\citep{wang2014keeping}}. PeCO always outperforms DiLCO for the three lower coverage ratios, moreover the -improvements grow with the network size. DiLCO outperforms PeCO when the coverage ratio is required to be $>90\%$, but PeCo extends the network lifetime significantly when coverage ratio can be relaxed.} -%DiLCO is better for coverage ratios near 100\%, but in that case PeCO is not ineffective for the smallest network sizes. +improvements grow with the network size. DiLCO outperforms PeCO when the coverage ratio is required to be $>90\%$, but PeCO extends the network lifetime significantly when coverage ratio can be relaxed.} \begin{figure}[h!] \centering \includegraphics[scale=0.55]{figure9.eps}