Social Forwarding in Large Scale Networks: Insights Based on Real Trace Analysis
Social forwarding, recently a hot topic in mobile opportunistic networking, faces extreme challenges from potentially large numbers of mobile nodes, vast areas, and limited communication resources. Such conditions render forwarding more challenging in large-scale networks. The authors observe that forwarding techniques based on social popularity fail to efficiently forward messages in large scale networks. The social popularity of nodes might not scale with the network size in a way that necessarily correlates with the contact opportunities and mobility patterns of these nodes. In this paper, they demonstrate, based on real mobility traces, the weakness of existing social forwarding algorithms in large scale communities. They address this weakness by proposing strategies for partitioning these large scale communities into sub-communities based on geographic locality or social interests.