{"title":"Vicinity-based DTN characterization","authors":"Tiphaine Phe-Neau, M. Amorim, V. Conan","doi":"10.1145/2159576.2159586","DOIUrl":null,"url":null,"abstract":"We relax the traditional definition of contact and intercontact times by bringing the notion of vicinity into the game. We propose to analyze disruption-tolerant networks (DTN) under the assumption that nodes are in k-contact when they remain within a few hops from each other and in k-intercontact otherwise (where k is the maximum number of hops characterizing the vicinity). We make interesting observations when analyzing several real-world and synthetic mobility traces. We detect a number of unexpected behaviors when analyzing k-contact distributions; in particular, we observe that in some datasets the average k-contact time decreases as we increase k. In fact, we observe that many nodes spend a non-negligible amount of time in each other's vicinity without coming into direct contact. We also show that a small k (typically between 3 and 4) is sufficient to capture most communication opportunities.","PeriodicalId":198518,"journal":{"name":"International Workshop on Mobile Opportunistic Networks","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"19","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Workshop on Mobile Opportunistic Networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2159576.2159586","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 19
Abstract
We relax the traditional definition of contact and intercontact times by bringing the notion of vicinity into the game. We propose to analyze disruption-tolerant networks (DTN) under the assumption that nodes are in k-contact when they remain within a few hops from each other and in k-intercontact otherwise (where k is the maximum number of hops characterizing the vicinity). We make interesting observations when analyzing several real-world and synthetic mobility traces. We detect a number of unexpected behaviors when analyzing k-contact distributions; in particular, we observe that in some datasets the average k-contact time decreases as we increase k. In fact, we observe that many nodes spend a non-negligible amount of time in each other's vicinity without coming into direct contact. We also show that a small k (typically between 3 and 4) is sufficient to capture most communication opportunities.