From: couturie Date: Fri, 13 Jan 2017 16:24:11 +0000 (+0100) Subject: no more color X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/JournalMultiPeriods.git/commitdiff_plain/refs/heads/master?ds=inline;hp=3835a7e1c5229e2f2711c7654ca42e05c2545617 no more color --- diff --git a/article.tex b/article.tex index 779bfe1..ed70b52 100644 --- a/article.tex +++ b/article.tex @@ -149,7 +149,7 @@ in~\cite{idrees2015distributed}. %more interesting to divide the area into several subregions, given the %computation complexity. -\textcolor{blue}{ Compared to our previous work~\cite{idrees2015distributed}, +\textcolor{black}{ Compared to our previous work~\cite{idrees2015distributed}, in this paper we study the possibility of dividing the sensing phase into multiple rounds. We make a multiround optimization, while previously it was a single round optimization. The idea is to @@ -291,7 +291,7 @@ Indeed, each sensor maintains its own timer and its wake-up time is randomized \subsection{Assumptions and primary points} \label{pp} -\textcolor{blue}{The assumptions and the coverage model are identical to those presented +\textcolor{black}{The assumptions and the coverage model are identical to those presented in~\cite{idrees2015distributed}. We consider a scenario in which sensors are deployed in high density to initially ensure a high coverage ratio of the interested area. Each sensor has a predefined sensing range $R_s$, an initial energy supply @@ -356,14 +356,14 @@ inside a subregion is less than or equal to 3. As can be seen in Figure~\ref{fig2}, our protocol works in periods fashion, where each period is divided into 4~phases: Information~Exchange, -Leader~Election, Decision, and Sensing. \textcolor{blue}{Compared to +Leader~Election, Decision, and Sensing. \textcolor{black}{Compared to the DiLCO protocol described in~\cite{idrees2015distributed},} each sensing phase is itself divided into $T$ rounds of equal duration and for each round a set of sensors (a cover set) is responsible for the sensing task. In this way a multiround optimization process is performed during each period after Information~Exchange and Leader~Election phases, in order to produce $T$ cover sets that will take the mission of sensing for $T$ -rounds. \textcolor{blue}{Algorithm~\ref{alg:MuDiLCO} is executed by each sensor +rounds. \textcolor{black}{Algorithm~\ref{alg:MuDiLCO} is executed by each sensor node~$s_j$ (with enough remaining energy) at the beginning of a period.} \begin{figure}[t!] \centering \includegraphics[width=125mm]{Modelgeneral.pdf} % 70mm @@ -400,7 +400,7 @@ rounds. \textcolor{blue}{Algorithm~\ref{alg:MuDiLCO} is executed by each sensor \label{alg:MuDiLCO} \end{algorithm} -\textcolor{blue}{As already described in~\cite{idrees2015distributed}}, two +\textcolor{black}{As already described in~\cite{idrees2015distributed}}, two types of packets are used by the proposed protocol: \begin{enumerate}[(a)] \item INFO packet: such a packet will be sent by each sensor node to all the @@ -482,7 +482,7 @@ determine the possibility of activating sensor $j$ during round $t$ of a given sensing phase. We also consider primary points as targets. The set of primary points is denoted by $P$ and the set of sensors by $J$. Only sensors able to be alive during at least one round are involved in the integer program. -\textcolor{blue}{Note that the proposed integer program is an +\textcolor{black}{Note that the proposed integer program is an extension of the one formulated in~\cite{idrees2015distributed}, variables are now indexed in addition with the number of round $t$.} @@ -657,11 +657,11 @@ lifetime. Moreover, it makes the MuDiLCO protocol more robust against random network disconnection due to node failures. However, too many subdivisions reduce the advantage of the optimization. In fact, there is a balance between the benefit from the optimization and the execution time needed to solve it. In -the following we have set the number of subregions to~16 \textcolor{blue}{as +the following we have set the number of subregions to~16 \textcolor{black}{as recommended in~\cite{idrees2015distributed}}. \subsection{Energy model} -\textcolor{blue}{The energy consumption model is detailed +\textcolor{black}{The energy consumption model is detailed in~\cite{raghunathan2002energy}. It is based on the model proposed by~\cite{ChinhVu}. We refer to the sensor node Medusa~II which uses an Atmels AVR ATmega103L microcontroller~\cite{raghunathan2002energy} to use numerical @@ -669,7 +669,7 @@ the following we have set the number of subregions to~16 \textcolor{blue}{as \subsection{Metrics} -\textcolor{blue}{To evaluate our approach we consider the performance metrics +\textcolor{black}{To evaluate our approach we consider the performance metrics detailed in~\cite{idrees2015distributed}, which are: Coverage Ratio, Network Lifetime and Energy Consumption. Compared to the previous definitions, formulations of Coverage Ratio and Energy Consumption are enriched with the @@ -752,7 +752,7 @@ points. The objective of this comparison is to select the suitable number of primary points to be used by a MuDiLCO protocol. In this comparison, MuDiLCO-1 protocol is used with five primary point models, each model corresponding to a number of primary points, which are called Model-5 (it uses 5 primary points), -Model-9, Model-13, Model-17, and Model-21. \textcolor{blue}{Note +Model-9, Model-13, Model-17, and Model-21. \textcolor{black}{Note that the results presented in~\cite{idrees2015distributed} correspond to Model-13 (13 primary points)}.