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dc.contributor.authorHernández-Orallo, Enrique
dc.contributor.authorMurillo Arcila, Marina 
dc.contributor.authorCano, Juan-Carlos
dc.contributor.authorT. Calafate, Carlos
dc.contributor.authorConejero, J.A.
dc.contributor.authorManzoni, Pietro
dc.contributor.otherMatemáticases_ES
dc.date.accessioned2025-02-13T08:01:19Z
dc.date.available2025-02-13T08:01:19Z
dc.date.issued2018
dc.identifier.issn2169-3536
dc.identifier.urihttp://hdl.handle.net/10498/35422
dc.description.abstractThe scarcity of bandwidth due to the explosive growth of mobile devices in 5G makes the offloading messaging workload to WiFi devices that use opportunistic connections, a very promising solution. Communications in mobile opportunistic networks take place upon the establishment of ephemeral contacts among mobile nodes using direct communication. In this paper we propose an analytical model based on population processes to evaluate data dissemination considering several parameters such as user density, contact rate, and the number of fixed nodes. From this model we obtain closed-form expressions for determining the diffusion time, the network coverage and the waiting time. Newer 5G wireless technologies like WiGig can offer multi-gigabit speeds, low latency, and security-protected connectivity between nearby devices. We therefore focus our work on the impact of high-speed and short-range wireless communications technologies for data dissemination in mobile opportunistic networks. Moreover, we test whether the coexistence with a fixed infrastructure can improve content dissemination, and thus justify its additional cost. Our results show that, when user density is high, the diffusion is mainly performed through the opportunistic contacts between mobile nodes, and that the diffusion coverage is close to 100\%. Moreover, the diffusion is fast enough to dynamically update the information among all the participating members, so users do not need to get closer to fixed spots for receiving updated information.es_ES
dc.formatapplication/pdfes_ES
dc.language.isoenges_ES
dc.publisherIEEEes_ES
dc.sourceIEEE Access, 6 (2018), 1603–1615es_ES
dc.subject5G mobile communicationes_ES
dc.subjectAnalytical modelses_ES
dc.subjectOpportunistic networkses_ES
dc.subjectContact-based Messaginges_ES
dc.subjectPerformance Evaluationes_ES
dc.titleAn Analytical Model Based on Population Processes to Characterize Data Dissemination in 5G Opportunistic Networkses_ES
dc.typejournal articlees_ES
dc.rights.accessRightsopen accesses_ES
dc.identifier.doi10.1109/ACCESS.2017.2779748
dc.type.hasVersionAMes_ES


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