Contacts-Aware Opportunistic Forwarding and data diffusion in Mobile Social Networks
Contacts-Aware Opportunistic Forwarding and data diffusion in Mobile Social Networks
#ContactsAwareOpportunisticForwarding #datadiffusion #MobileSocialNetworks
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Exploiting community structure for opportunistic
forwarding decisions in mobile social networks offers a promising
paradigm to improve the transmission performance and reduce
the extra network overhead. Actually, people will have closer
relationships and more opportunities to contact with each other
if they are in the same community. In this paper, the activeness
of nodes and the probability of reaching the destination are
investigated based on the node contacts in the trace. Then
the Contacts-Aware Opportunistic Forwarding (CAOF) scheme,
which includes inter-community and intra-community phase, is
proposed. In the inter-community phase, the node with higher
global activeness and source-to-destination probability is selected
to serve as the relay. Besides, in the intra-community phase,
the forwarding decisions are determined by the local metrics.
Furthermore, we compare the proposed CAOF scheme with
several benchmark forwarding algorithms, including BUBBLE
Rap, SPRINT, Epidemic and JDER. The validity of the modeling
and the soundness of the analysis are verified through extensive
experiments with real traces, which illustrates that it outperforms
other routing strategies in heavy traffic scenarios.
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