Cluster head selection method for content‐centric mobile social network in 5G. Issue 4 (26th February 2018) - Tulu, Muluneh M.; Hou, Ronghui; Li, Chuanyin; Amentie, Melkamu D.
Abstract : In a social network, spreading information through the powerful leader of the community is highly valuable. Applying effective methods to identify influential nodes will leverage cellular networks in device‐to‐device local communication. In this study, entropy of betweenness centrality (EBC) combining the degree of the node and the degree of the neighbour node is proposed as a metric to select nodes from large and complex networks to disseminate information easily. EBC describes how the node is essential to connect two regions of the network. In the authors' work, nodes are identified by EBC, which is evaluated by susceptible‐infected (SI) model. Hence, if the source of infection in the SI model is one node and the percentage of infected nodes is the largest, which means that the source node is the most powerful node in the network. Simulation results show that the proposed method performs better than the existing methods to spread information in the mobile social network.