{"title":"Boundary and holes recognition in wireless sensor networks","authors":"Rachid Beghdad, Amar Lamraoui","doi":"10.1016/j.jides.2016.04.001","DOIUrl":null,"url":null,"abstract":"<div><p>In this paper, a distributed solution is proposed for detecting boundaries and holes in the WSN using only the nodes connectivity information. The run of our protocol is divided imto three main steps. In the first step, each node collects connectivity information of its one-hop neighbors and constructs its one-hop neighbors’ graph. In the second step, independent sets are constructed. In the last step, the independent sets are connected in order to find the closed path. Therefore, the node can make its own decision to be an internal or a boundary node. Simulation results show that our algorithm can detect fine-grained boundaries with high accuracy, low energy consumption and less communication overhead compared to some former works. In addition, this algorithm performs better than some exiting approaches (BCP, THD, and SDBR).</p></div>","PeriodicalId":100792,"journal":{"name":"Journal of Innovation in Digital Ecosystems","volume":"3 1","pages":"Pages 1-14"},"PeriodicalIF":0.0000,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.jides.2016.04.001","citationCount":"40","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Innovation in Digital Ecosystems","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352664516300013","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 40
Abstract
In this paper, a distributed solution is proposed for detecting boundaries and holes in the WSN using only the nodes connectivity information. The run of our protocol is divided imto three main steps. In the first step, each node collects connectivity information of its one-hop neighbors and constructs its one-hop neighbors’ graph. In the second step, independent sets are constructed. In the last step, the independent sets are connected in order to find the closed path. Therefore, the node can make its own decision to be an internal or a boundary node. Simulation results show that our algorithm can detect fine-grained boundaries with high accuracy, low energy consumption and less communication overhead compared to some former works. In addition, this algorithm performs better than some exiting approaches (BCP, THD, and SDBR).