Web of Science: 17 citations, Scopus: 22 citations, Google Scholar: citations
Hey, Influencer! Message Delivery to Social Central Nodes in Social Opportunistic Networks
Borrego Iglesias, Carlos (Universitat Autònoma de Barcelona. Departament d'Enginyeria de la Informació i de les Comunicacions)
Borrell i Viader, Joan (Universitat Autònoma de Barcelona. Departament d'Enginyeria de la Informació i de les Comunicacions)
Robles, Sergi (Universitat Autònoma de Barcelona. Departament d'Enginyeria de la Informació i de les Comunicacions)

Date: 2019
Abstract: This paper presents a new strategy to efficiently deliver messages to influencers in social opportunistic networks. An influencer node is an important node in the network with a high social centrality and, as a consequence, it can have some characteristics such as high reputation, trustfulness and credibility, that makes it an interesting recipient. Social network analysis has already been used to improve routing in opportunistic networking, but there are no mechanisms to efficiently route and deliver messages to these network influencers. The delivery strategy proposed in this article uses optimal stopping statistical techniques to choose among the different delivery candidate nodes in order to maximise the social centrality of the node chosen for delivery. For this decision process, we propose a routing-delivery strategy that takes into account node characteristics such as how central a node is in terms of its physical encounters. We show, by means of simulations based on real traces and message exchange datasets, that our proposal is efficient in terms of influencer selection, overhead, delivery ratio and latency time. With the proposed strategy, a new venue of applications for opportunistic networks can be devised and developed using the leading figure of social influencers.
Grants: Agència de Gestió d'Ajuts Universitaris i de Recerca 2017/SGR-463
Ministerio de Ciencia e Innovación TIN2017-87211-R
Rights: Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades. Creative Commons
Language: Anglès
Document: Article ; recerca ; Versió acceptada per publicar
Subject: OppNet ; Opportunistic social networks ; Optimisation ; Centrality
Published in: Computer Communications, Vol. 137 (March 2019) , p. 81-91, ISSN 0140-3664

DOI: 10.1016/j.comcom.2019.02.003


Postprint
15 p, 4.2 MB

The record appears in these collections:
Research literature > UAB research groups literature > Research Centres and Groups (research output) > Engineering > Security of Networks and Distributed Applications (SENDA)
Articles > Research articles
Articles > Published articles

 Record created 2019-03-02, last modified 2022-03-05



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