From 685190fa243f31d4bb41e47f85d85928b35ed11c Mon Sep 17 00:00:00 2001 From: Karine Deschinkel Date: Thu, 8 Oct 2015 15:34:29 +0200 Subject: [PATCH] ok --- reponse.tex | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/reponse.tex b/reponse.tex index afa144f..a909f46 100644 --- a/reponse.tex +++ b/reponse.tex @@ -85,7 +85,7 @@ This work proposed a distributed lifetime coverage optimization (DiLCO) protocol sub-areas, and assigning a single cluster head in each sub-area to achieve more balanced energy dissipation. Hence, I suggest that the authors could clearly state the differences and benefits between their leader selection technique and the methods of cluster head election in LEACH or other distributed protocols. Moreover, they used the two protocols, DESK and GAF, for assessing the performance of their protocols is not convincible. The authors may include more well-known or recently developed protocols for comparison. -\textcolor{blue}{\textbf{\textsc{Answer :} The difference between our leader selection technique and the methods of cluster head election in LEACH or other distributed protocols in that our approach assumes that the sensors are deployed almost uniformly and with high density over the region. So we only need to fix a regular division of the region into subregions to make the problem tractable. The subdivision is made using divide-and-conquer concept such that the number of hops between any pairs of sensors inside a subregion is less than or equal to~3. The sensors inside each subregion cooperate to elect one leader. Leader applies sensor activity scheduling based optimization to provide the schedule to the sensor nodes in the subregion. The advantage of our approach is to minimize the energy consumption required for communication. The sensors only require to communicate with the other sensors inside the subregion to elect the leader instead of communicating with other nodes in the WSN. \\Whereas in LEACH and other cluster head election methods, the cluster heads are elected in distributed way where sensors elect themselves to be local cluster-heads at any given time with a certain probability. These cluster-head nodes broadcast their status to the other sensors in the network. Each sensor node determines to which cluster it wants to belong by choosing the cluster-head that requires the minimum communication energy. Once all the nodes are organized into clusters, each cluster-head creates a schedule for the nodes in its cluster. \\\\ +\textcolor{green}{\textbf{\textsc{Answer :} The difference between our leader selection technique and the methods of cluster head election in LEACH or other distributed protocols in that our approach assumes that the sensors are deployed almost uniformly and with high density over the region. So we only need to fix a regular division of the region into subregions to make the problem tractable. The subdivision is made using divide-and-conquer concept such that the number of hops between any pairs of sensors inside a subregion is less than or equal to~3. The sensors inside each subregion cooperate to elect one leader. Leader applies sensor activity scheduling based optimization to provide the schedule to the sensor nodes in the subregion. The advantage of our approach is to minimize the energy consumption required for communication. The sensors only require to communicate with the other sensors inside the subregion to elect the leader instead of communicating with other nodes in the WSN. \\Whereas in LEACH and other cluster head election methods, the cluster heads are elected in distributed way where sensors elect themselves to be local cluster-heads at any given time with a certain probability. These cluster-head nodes broadcast their status to the other sensors in the network. Each sensor node determines to which cluster it wants to belong by choosing the cluster-head that requires the minimum communication energy. Once all the nodes are organized into clusters, each cluster-head creates a schedule for the nodes in its cluster. \\\\ In fact, GAF algorithm is chosen for comparison as a competitor because it is famous and easy to implement, as well as many authors referred to it in many publications. DESK algorithm is also selected as competitor in the comparison because it works into rounds fashion (network lifetime divided into rounds) similar to our approaches, as well as DESK is a full distributed coverage approach. }} -- 2.39.5