To investigate how consensus is reached on a large self-organized
peer-to-peer network, we extended the naming game model commonly used in
language and communication to Naming Game in Groups (NGG). Differing from other
existing naming game models, in NGG, everyone in the population (network) can
be both speaker and hearer simultaneously, which resembles in a closer manner
to real-life scenarios. Moreover, NGG allows the transmission (communication)
of multiple words (opinions) for multiple intra-group consensuses. The
communications among indirectly-connected nodes are also enabled in NGG. We
simulated and analyzed the consensus process in some typical network
topologies, including random-graph networks, small-world networks and
scale-free networks, to better understand how global convergence (consensus)
could be reached on one common word. The results are interpreted on group
negotiation of a peer-to-peer network, which shows that global consensus in the
population can be reached more rapidly when more opinions are permitted within
each group or when the negotiating groups in the population are larger in size.
The novel features and properties introduced by our model have demonstrated its
applicability in better investigating general consensus problems on
peer-to-peer networks.Comment: 11 pages, 6 figure