TY - JOUR
T1 - Hey, influencer! Message delivery to social central nodes in social opportunistic networks
AU - Borrego, Carlos
AU - Borrell, Joan
AU - Robles, Sergi
PY - 2019/3/1
Y1 - 2019/3/1
N2 - © 2019 Elsevier B.V. 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.
AB - © 2019 Elsevier B.V. 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.
KW - Centrality
KW - OppNet
KW - Opportunistic social networks
KW - Optimisation
UR - http://www.mendeley.com/research/hey-influencer-message-delivery-social-central-nodes-social-opportunistic-networks
UR - https://www.scopus.com/pages/publications/85062021581
U2 - 10.1016/j.comcom.2019.02.003
DO - 10.1016/j.comcom.2019.02.003
M3 - Article
SN - 0140-3664
VL - 137
SP - 81
EP - 91
JO - Computer Communications
JF - Computer Communications
ER -