Social-Similarity-based Multicast Algorithm in impromptu mobile social networks

Mobile social networks (MSNs) where people contact each other through mobile devices have become increasingly popular. In this paper, we study a special kind of MSNs formed impromptu when people gather together at conferences, social events, etc. Multicast is an important routing service which supports the dissemination of messages to a group of users. Most of the existing related multicast algorithms are designed for general Delay Tolerant Networks (DTNs) where social factors are neglected. Recently, a social-profile-based multicast (SPM) protocol that utilizes the static social features in user profiles has been proposed. We believe that in a dynamic environment such as the IMSN, static social features may not reflect people´s dynamic behavior. Therefore, in this paper, we propose a novel Social-Similarity-based Multicast Algorithm (Multi-Sosim) using nodes´ dynamic social features and a compare-split scheme to improve multicast efficiency in IMSNs. Simulation results using a real trace show that our algorithm outperforms its variations and the existing one using static social features.