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dc.contributor.authorFazio, Peppino
dc.contributor.authorMehić, Miralem
dc.contributor.authorVozňák, Miroslav
dc.contributor.authorDe Rango, Floriano
dc.contributor.authorTropea, Mauro
dc.date.accessioned2023-12-18T07:36:47Z
dc.date.available2023-12-18T07:36:47Z
dc.date.issued2023
dc.identifier.citationComputer Networks. 2023, vol. 226, art. no. 109689.cs
dc.identifier.issn1389-1286
dc.identifier.issn1872-7069
dc.identifier.urihttp://hdl.handle.net/10084/151841
dc.description.abstractNowadays, mobile computing has become a key component of telecommunication systems, and the Open Systems Interconnection (OSI) layer operations are affected by the effects of node movements along the roads, from the physical to the routing/transport layers. In particular, routing approaches have been investigated from many years, trying to optimize the performance of the whole considered system, under different points of view. In this paper we are focusing the attention on the analysis of the mobility grade trend for a mobile ad-hoc network environment, as well as on the way it can be a-priori known, in order to have the possibility to study how the dynamics of mobile nodes can be described and in-advance known, with a predicted knowledge of nodes stability (in terms of mobility). Our simulations considered mobility in real geographical maps, and the obtained results confirmed the goodness of our proposed study.cs
dc.language.isoencs
dc.publisherElseviercs
dc.relation.ispartofseriesComputer Networkscs
dc.relation.urihttps://doi.org/10.1016/j.comnet.2023.109689cs
dc.rights© 2023 The Authors. Published by Elsevier B.V.cs
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/cs
dc.subjectmobile networkscs
dc.subjectmobilitycs
dc.subjectroutingcs
dc.subjectnetworkingcs
dc.subjectmetriccs
dc.subjectstabilitycs
dc.titleA novel predictive approach for mobility activeness in mobile wireless networkscs
dc.typearticlecs
dc.identifier.doi10.1016/j.comnet.2023.109689
dc.rights.accessopenAccesscs
dc.type.versionpublishedVersioncs
dc.type.statusPeer-reviewedcs
dc.description.sourceWeb of Sciencecs
dc.description.volume226cs
dc.description.firstpageart. no. 109689cs
dc.identifier.wos000955376900001


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© 2023 The Authors. Published by Elsevier B.V.
Except where otherwise noted, this item's license is described as © 2023 The Authors. Published by Elsevier B.V.