X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/Sensornets15.git/blobdiff_plain/d7d5c33508ae16b9109c73481cb704710c4007c8..007e5f7388cc223a5c2c79abf8c2342ecefbbd26:/reponse.tex?ds=sidebyside

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@@ -85,8 +85,13 @@ 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{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. }}
+\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.   \\\\
+In our approach, the leader selection technique is quite different from the LEACH protocol or from its variants. Contrary to the LEACH protocol, the division of the area of interest into subregions is assumed to be performed before the head election. Moreover we assume that sensors are deployed almost uniformly and with high density over the area of interest, such that the division is fixed and regular. As in LEACH, our protocol works in round fashion. In each round, during the pre-sensing phase, nodes make autonomous decisions. In LEACH, each sensor elects itself to be a cluster head, and each non-cluster head will determine its cluster for the round.  In our protocol, nodes in the same subregion select their leader. In both protocols, the amount of remaining energy in each node is taken into account to promote the nodes that have the most energy to become leader. Contrary to the LEACH protocol where all sensors will be active during the sensing-phase, our protocol allows to deactivate a subset of sensors through an optimization process which reduces significantly the energy consumption. \\\\
+As explained by the reviewer, there is a large variety of energy-efficient protocols for WSN. We focus on GAF and DESK protocols for two main points. First,  our protocol is inspired from the two other ones. DiLCO uses a regular division of the area as in GAF protocol and a temporal division in rounds as in DESK algorithm. Secondly, GAF and DESK are well-known protocols, easy to implement, and often used as references for comparison. \textcolor{red}{je ne sais pas si on ne devrait pas inclure une ref Ã  LEACH dans la biblio, mais je ne sais pas trop comment l'introduire dans le papier...}
+ \\\\
+}}
+%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. }}
 
 
 
