Community and Social Feature-Based Multicast in Opportunistic Mobile Social Networks

Abstract

Opportunistic Mobile Social Networks (OMSNs), formed by people moving around carrying mobile devices such as smartphones, PDAs, and laptops, have become popular in recent years. The OMSNs we discuss here are a special kind of delay tolerant networks (DTNs) that help enhance spontaneous interaction and communication among users that opportunistically encounter each other, without additional infrastructure support. Multicast is an important routing service in OMSNs which supports the dissemination of messages to a group of users. Most of the existing multicast algorithms are designed for general-purpose DTNs where social factors are neglected or reflected in static social features which are not updated to catch nodes' dynamic contact behavior. In this paper, we introduce the concept of dynamic social features and its enhancement to capture nodes' dynamic contact behavior, consider more social relationships among nodes, and adopt the community structure in the multicast compare-split scheme to select the best relay node for each destination in each hop to improve multicast efficiency. We propose two multicast algorithms based on these new features. The first community and social feature-based multicast algorithm is called Multi-CSDO which involves destination nodes only in community detection, and the second one is called Multi-CSDR which involves both the destination nodes and the relay candidates in community detection. The analysis of the algorithms is given and simulation results using a real trace of an OMSN show that our new algorithms outperform the existing one in terms of delivery rate, latency, and number of forwardings.