From fe3d4f5c7954d683dbfbc1f26de2d724ff9889d7 Mon Sep 17 00:00:00 2001 From: couturie Date: Mon, 12 Aug 2013 21:42:11 +0200 Subject: [PATCH] new --- bare_conf.tex | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) diff --git a/bare_conf.tex b/bare_conf.tex index a6cc277..fd7001e 100755 --- a/bare_conf.tex +++ b/bare_conf.tex @@ -661,7 +661,7 @@ the maximum number of points are covered during each round. \section{\uppercase{Simulation Results}} \label{exp} -In this section, we conducted a series of simulations, to evaluate the +In this section, we conducted a series of simulations to evaluate the efficiency and relevance of our approach, using the discrete event simulator OMNeT++ \cite{varga}. We performed simulations for five different densities varying from 50 to 250~nodes. Experimental results @@ -683,7 +683,7 @@ range 24-60~joules, and each sensor node will consume 0.2 watts during the sensing period which will have a duration of 60 seconds. Thus, an active node will consume 12~joules during sensing phase, while a sleeping node will use 0.002 joules. Each sensor node will not -participate in the next round if it's remaining energy is less than 12 +participate in the next round if its remaining energy is less than 12 joules. In all experiments the parameters are set as follows: $R_s=5m$, $w_{\Theta}=1$, and $w_{U}=|P^2|$. @@ -711,7 +711,7 @@ number of rounds on the average coverage ratio for 150 deployed nodes for the three approaches. It can be seen that the three approaches give similar coverage ratios during the first rounds. From the 9th~round the coverage ratio decreases continuously with the simple -heuristic, while the other two strategies provide superior coverage to +heuristic, while the two other strategies provide superior coverage to $90\%$ for five more rounds. Coverage ratio decreases when the number of rounds increases due to dead nodes. Although some nodes are dead, thanks to strategy~1 or~2, other nodes are preserved to ensure the @@ -791,14 +791,14 @@ expected, the Strategy with One Leader is usually slightly better than the second strategy, because the global optimization permit to turn off more sensors. Indeed, when there are two subregions more nodes remain awake near the border shared by them. Note that again as the -number of rounds increase the two leader strategy becomes the most +number of rounds increases the two leader strategy becomes the most performing, since its takes longer to have the two subregion networks simultaneously disconnected. \subsection{The Network Lifetime} We have defined the network lifetime as the time until all nodes have -been drained of their energy or each sensor network monitoring a area +been drained of their energy or each sensor network monitoring an area becomes disconnected. In figure~\ref{fig6}, the network lifetime for different network sizes and for the three approaches is illustrated. @@ -815,10 +815,10 @@ As highlighted by figure~\ref{fig6}, the network lifetime obviously increases when the size of the network increase, with our approaches that lead to the larger lifetime improvement. By choosing for each round the well suited nodes to cover the region of interest and by -leaving sleep the other ones to be used later in next rounds, both +letting the other ones sleep in order to be used later in next rounds, both proposed strategies efficiently prolong the lifetime. Comparison shows -that the larger the sensor number, the more our strategies outperform -the heuristic. Strategy~2, which uses two leaders, is the best one +that the larger the sensor number is, the more our strategies outperform +the simple heuristic. Strategy~2, which uses two leaders, is the best one because it is robust to network disconnection in one subregion. It also means that distributing the algorithm in each node and subdividing the sensing field into many subregions, which are managed -- 2.39.5