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[LiCO.git] / PeCO-EO / articleeo.tex

diff --git a/PeCO-EO/articleeo.tex b/PeCO-EO/articleeo.tex
index 0d70e08c1ed2a7a0753f55b6f6aab76a92f13939..5ba7f55932dd982a40e034a21050950216875f02 100644 (file)
--- a/PeCO-EO/articleeo.tex
+++ b/PeCO-EO/articleeo.tex
@@ -506,7 +506,8 @@ $RE_k$, which must be greater than  a threshold $E_{th}$ in order to participate
 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,
 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}{We suppose that 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 their 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)}
+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).}

 The sensors  inside a same  region cooperate to  elect a leader.   The selection
 criteria for the leader are (in order  of priority):
 \begin{enumerate}
 The sensors  inside a same  region cooperate to  elect a leader.   The selection
 criteria for the leader are (in order  of priority):
 \begin{enumerate}


@@ -719,7 +720,7 @@ approach.
   of sensors in the network.
   
 \item {\bf \textcolor{blue}{Energy Saving Ratio (ESR)}}:  
   of sensors in the network.
   
 \item {\bf \textcolor{blue}{Energy Saving Ratio (ESR)}}:  

-\textcolor{blue}{we consider a performance metric linked to energy. This metric, called Energy Saving Ratio (ESR), is defined by:
+\textcolor{blue}{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}}
 \begin{equation*}
 \scriptsize
 \mbox{ESR}(\%) = \frac{\mbox{Number of alive sensors during this round}}


@@ -854,8 +855,24 @@ keeping a greater coverage ratio as shown in Figure \ref{figure5}.
 
 \subsubsection{\textcolor{blue}{Energy Saving Ratio (ESR)}} 
 
 
 \subsubsection{\textcolor{blue}{Energy Saving Ratio (ESR)}} 
 

-\textcolor{blue}{In this experiment, we consider an Energy Saving Ratio (see Figure~\ref{fig5}) for 200 deployed nodes. 
-The  longer the ratio  is,  the more  redundant sensor  nodes are switched off, and consequently  the longer the  network may  live. }
+%\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.}

 
 \begin{figure}[h!]
 %\centering
 
 \begin{figure}[h!]
 %\centering


@@ -866,8 +883,6 @@ The  longer the ratio  is,  the more  redundant sensor  nodes are switched off,
 \label{fig5}
 \end{figure} 
 
 \label{fig5}
 \end{figure} 
 

-\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 balance the energy consumption among sensor nodes inside each small fixed grid that 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 togehter. After that GAF provide less energy saving compared with other approches because of the large number of dead nodes. DESK algorithm shows less energy saving compared with other approaches due to activate a larg number of sensors during the sensing. DiLCO protocol provides less energy saving ratio commpared 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{Energy Consumption}
 
 
 \subsubsection{Energy Consumption}


@@ -921,16 +936,17 @@ time, and the lifetime with a coverage over 50\% is far longer than with 95\%.
 \end{figure} 
 
 Figure~\ref{figure9} compares the lifetime coverage  of the DiLCO and PeCO protocols
 \end{figure} 
 
 Figure~\ref{figure9} compares the lifetime coverage  of the DiLCO and PeCO protocols

-for  different   coverage  ratios.   We  denote  by   Protocol/50,  Protocol/80,
+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
 Protocol/85, Protocol/90,  and Protocol/95 the  amount of time during  which the

-network  can satisfy  an  area  coverage greater  than  $50\%$, $80\%$,  $85\%$,
+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
 area to be  monitored. For example, forest
 fire application might require complete coverage
 $90\%$, 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
 area to be  monitored. For example, forest
 fire application might require complete coverage

-in summer seasons while only requires 80$\%$ of the area to be covered in rainy seasons \cite{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 \cite{vu2009universal}. 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\cite{wang2014keeping}}. PeCO might be  an interesting method since  it achieves a good balance  between a high level  coverage ratio  and network  lifetime. PeCO
-always  outperforms DiLCO  for the  three  lower coverage  ratios, moreover  the
-improvements grow  with the network  size. \textcolor{blue}{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.}
+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.
 
 \begin{figure}[h!]
 %DiLCO  is better for  coverage ratios near 100\%, but  in that case PeCO  is not ineffective for  the smallest network sizes.
 
 \begin{figure}[h!]


@@ -1013,6 +1029,6 @@ received support. This work is also partially funded by the Labex ACTION program
 (contract ANR-11-LABX-01-01).  
  
 \bibliographystyle{gENO}
 (contract ANR-11-LABX-01-01).  
  
 \bibliographystyle{gENO}

-\bibliography{articleeo} % biblio
+\bibliography{biblio} %articleeo

 
 \end{document}
 
 \end{document}