X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/ThesisAli.git/blobdiff_plain/a19450b98a8865b2c2b11438256bd9e51e0448f7..dd42ca97656c19804fa0624b8e9095293f58976f:/CHAPITRE_02.tex diff --git a/CHAPITRE_02.tex b/CHAPITRE_02.tex index 5b7f45d..7aaafbe 100644 --- a/CHAPITRE_02.tex +++ b/CHAPITRE_02.tex @@ -102,6 +102,14 @@ The works presented in~\cite{ref134,ref135,ref136} focus on coverage-aware, dist Shibo et al.~\cite{ref137} have expressed the coverage problem as a minimum weight submodular set cover problem and proposed a Distributed Truncated Greedy Algorithm (DTGA) to solve it. They take advantage from both temporal and spatial correlations between data sensed by different sensors, and leverage prediction, to improve the lifetime. +In \cite{ref160} authors transform the area coverage problem to the target +coverage one taking into account the intersection points among disks of sensors +nodes or between disk of sensor nodes and boundaries. + + +In \cite{ref133} authors prove that if the perimeters of sensors are sufficiently covered it will be the case for the whole area. They provide an algorithm in $O(nd~log~d)$ time to compute the perimeter-coverage of +each sensor, where $d$ denotes the maximum number of sensors that are neighboring to a sensor and $n$ is the total number of sensors in the network. + In \cite{ref84}, Xu et al. have described an algorithm, called Geographical Adaptive Fidelity (GAF), which uses geographic location information to divide the area of interest into fixed square grids. Within each grid, it keeps only one node staying awake to take the responsibility of sensing and communication. Figure~\ref{gaf1} gives an example of fixed square grid in GAF. @@ -248,12 +256,16 @@ check if its $n_i$ is decreased to 0 or not. If $n_i$ of a sensor node is 0 (i.e & \tiny L. Zhang et al. (2013)~\cite{ref136} & \OK & & \OK & & & \OK & \OK & & \OK & & \OK & &\\ -& \tiny S. He et al. (2012)~\cite{ref137} & \OK & \OK & \OK & & & & \OK & & \OK & & & &\\ +& \tiny S. He et al. (2012)~\cite{ref137} & \OK & \OK & \OK & & & & \OK & & \OK & & & &\\ & \tiny Y. Xu et al. (2001)~\cite{ref84} & \OK & & \OK & & & & \OK & & \OK & & & &\\ & \tiny C. Vu et al. (2006)~\cite{ref132} & \OK & & \OK & & \OK & & \OK & & \OK & & \OK & &\\ +& \tiny X. Deng et al. (2012)~\cite{ref160} & \OK & & \OK & & & & \OK & & \OK & & & &\\ + +& \tiny X. Deng et al. (2005)~\cite{ref133} & \OK & & \OK & & \OK & & \OK & & \OK & & & &\\ + &\textbf{\textcolor{red}{ \tiny DiLCO Protocol (2014)}} & \textbf{\textcolor{red}{\OK}} & & \textbf{\textcolor{red}{\OK}} & & & \textbf{\textcolor{red}{\OK}} & \textbf{\textcolor{red}{\OK}} & & & &\textbf{\textcolor{red}{\OK}} & & \\ &\textbf{\textcolor{red}{ \tiny MuDiLCO Protocol (2014)}} & \textbf{\textcolor{red}{\OK}} & & \textbf{\textcolor{red}{\OK}} & & & \textbf{\textcolor{red}{\OK}} & \textbf{\textcolor{red}{\OK}} & & & \textbf{\textcolor{red}{\OK}} &\textbf{\textcolor{red}{\OK}} & & \\ @@ -271,6 +283,7 @@ check if its $n_i$ is decreased to 0 or not. If $n_i$ of a sensor node is 0 (i.e + \section{Conclusion} \label{ch2:sec:05} This chapter has been described some coverage problems proposed in the literature, and their assumptions and proposed solutions.