X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/UIC2013.git/blobdiff_plain/8122e0cee2d1c24eb33b2646bb579111dd9abcbb..refs/heads/master:/bare_conf.tex?ds=sidebyside diff --git a/bare_conf.tex b/bare_conf.tex index a38a894..bbe85c3 100644 --- a/bare_conf.tex +++ b/bare_conf.tex @@ -67,7 +67,7 @@ subregions using a divide-and-conquer method and then the scheduling of sensor node activity is planned for each subregion. The proposed scheduling considers rounds during which a small number of nodes, remaining active for sensing, is selected to ensure coverage. Each -round consists of four phases: (i)~Information Exchange, (ii)~Leader +round consists in four phases: (i)~Information Exchange, (ii)~Leader Election, (iii)~Decision, and (iv)~Sensing. The decision process is carried out by a leader node, which solves an integer program. Simulation results show that the proposed approach can prolong the @@ -120,7 +120,7 @@ the network lifetime, while achieving acceptable quality of service for applications. Indeed, sensors nodes have limited resources in terms of memory, energy and computational power. -Since sensor nodes have limited battery life and without being able to +Since sensor nodes have limited battery life and since it is impossible to replace batteries, especially in remote and hostile environments, it is desirable that a WSN should be deployed with high density because spatial redundancy can then be exploited to increase the lifetime of @@ -179,7 +179,7 @@ from both temporal and spatial correlations between data sensed by different sensors. The works presented in \cite{Bang, Zhixin, Zhang} focus on the -definition of a coverage-aware, distributed energy-efficient and +definition of coverage-aware, distributed energy-efficient and distributed clustering methods respectively. They aim to extend the network lifetime while ensuring the coverage. S. Misra et al. \cite{Misra05} proposed a localized algorithm which conserves energy and @@ -197,8 +197,7 @@ to build a scheduling strategy.\\ %\begin{itemize} %\item {\indent \bf How must the phases for information exchange, decision - and sensing be planned over time?} Our algorithm divides the time -line into rounds. Each round contains 4 phases: Information Exchange, + and sensing be planned over time?} Our algorithm divides the timeline into rounds. Each round contains 4 phases: Information Exchange, Leader Election, Decision, and Sensing. %\item @@ -688,7 +687,7 @@ nodes. Overall, to be able to deal with very large networks, a distributed method is clearly required. \begin{table}[ht] -\caption{EXEC. TIME(S) VS. NUMBER OF SENSORS} +\caption{EXECUTION TIME(S) VS. NUMBER OF SENSORS} % title of Table \centering @@ -777,8 +776,8 @@ propose allows to reduce the difficulty of a single global optimization problem by partitioning it in many smaller problems, one per subregion, that can be solved more easily. In future work, we plan to study a coverage protocol which computes all active sensor -schedules in one time, using optimization methods such as swarms -optimization or evolutionary algorithms. +schedules in only one step for many rounds, using optimization methods +such as swarms optimization or evolutionary algorithms. % use section* for acknowledgement %\section*{Acknowledgment}