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Modeling opportunistic communication with churn
KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0002-3704-1338
2016 (English)In: Computer Communications, ISSN 0140-3664, E-ISSN 1873-703XArticle in journal (Refereed) Published
Abstract [en]

In opportunistic networking, characterizing contact patterns between mobile users is essential for assessing feasibility and performance of opportunistic applications. There has been significant efforts in deriving this characterization, based on observations and trace analyses; however, most of the previously established results were obtained by studying contact opportunities at large spatial and temporal scales. Moreover, the user population is considered to be constant: no user can join or leave the system. Yet, there are many examples of scenarios which do not fully adhere to the previous assumption and cannot be accurately described at large scales. Urban environments, such as smaller city districts, are characterized by highly dynamic user populations. We believe that scenarios with varying population require further investigation. In this paper, we present a novel modeling approach to study operation of opportunistic applications in scenarios where the population size is subjected to frequent changes, that is, it exhibits churn. We examine two location-based content sharing schemes: a purely opportunistic case and an infrastructure-supported content sharing scheme, for which we provide stochastic models based on stochastic differential equations (SDEs). We validate our models in five scenarios: a city area, subway station, conference, campus, and a scenario with a synthetic mobility model and we show that the models provide good representations of the investigated scenarios. © 2016.

Place, publisher, year, edition, pages
Elsevier, 2016.
Keyword [en]
Churn, Content sharing, Opportunistic networks, Stochastic differential equations, Stochastic models, Differential equations, Population statistics, Stochastic systems, Subway stations, Trace analysis, Opportunistic communications, Opportunistic networking, Spatial and temporal scale, Urban environments
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
URN: urn:nbn:se:kth:diva-196165DOI: 10.1016/j.comcom.2016.04.018ISI: 000389163700013ScopusID: 2-s2.0-84965146842OAI: diva2:1046958

Correspondence Address: Pajevic, QC 20161116

Available from: 2016-11-16 Created: 2016-11-14 Last updated: 2017-01-09Bibliographically approved

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Pajevic, LjubicaKarlsson, Gunnar
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