From a96a3c20a51ff741b0b50ea566e9fab35f311ea1 Mon Sep 17 00:00:00 2001 From: couturie Date: Thu, 15 Aug 2013 15:51:57 +0200 Subject: [PATCH] new --- bare_conf.tex | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/bare_conf.tex b/bare_conf.tex index 0804bff..50c500f 100755 --- a/bare_conf.tex +++ b/bare_conf.tex @@ -630,7 +630,7 @@ X_{j} \in \{0,1\}, &\forall j \in J The first group of constraints indicates that some primary point $p$ should be covered by at least one sensor and, if it is not always the case, overcoverage and undercoverage variables help balancing the -restriction equation by taking positive values. There are two main %%RAPH restriction equations???? +restriction equations by taking positive values. There are two main objectives. First we limit the overcoverage of primary points in order to activate a minimum number of sensors. Second we prevent the absence of monitoring on some parts of the subregion by minimizing the undercoverage. The @@ -860,7 +860,7 @@ communications have a small impact on the network lifetime. A sensor node has limited energy resources and computing power, therefore it is important that the proposed algorithm has the shortest possible execution time. The energy of a sensor node must be mainly -used for the sensing phase, not for the pre-sensing ones. %%RAPH: plusieurs phase de pre-sensing?? +used for the sensing phase, not for the pre-sensing ones. Table~\ref{table1} gives the average execution times in seconds on a laptop of the decision phase (solving of the optimization problem) during one round. They are given for the different approaches and -- 2.39.5