Efficient Multicast Algorithms in Opportunistic Mobile Social Networks using Community and Social Features

Opportunistic Mobile Social Networks (OMSNs), formed by people moving around carrying mobile devices, enhance spontaneous communication among users that opportunistically encounter each other without additional infrastructure. Multicast is an important communication service in OMSNs. Most of the existing multicast algorithms neglect or adopt static social factors that are inadequate to catch nodes’ dynamic contact behavior. In this paper, we introduce dynamic social features and its enhancement to capture nodes’ contact behavior, consider more social relationships among nodes, and adopt community structure in the multicast compare-split schemes to select the best relay nodes to improve multicast efficiency. We propose two multicast algorithms based on these new features. The first one Multi-CSDO involves destination nodes only in community detection while the second one Multi-CSDR involves both the destination nodes and the relay candidates in community detection. The analysis of the algorithms is given and simulation results using two real OMSN traces show that our new algorithms outperform the existing ones in delivery rate, latency, and number of forwardings.