Efficient Data Forwarding in Mobile Social Networks with Diverse Connectivity Characteristics

Abstract

Mobile Social Network (MSN) with diverse connectivity characteristics is a combination of opportunistic network and mobile ad hoc network. Since the major difficulty of data forwarding is the opportunistic part, techniques designed for opportunistic networks are commonly used to forward data in MSNs. However, this may not be the best solution since they do not consider the ubiquitous existences of Transient Connected Components (TCCs), where nodes inside a TCC can reach each other by multi-hop wireless communications. In this paper, we first identify the existence of TCCs and analyze their properties based on five real traces. Then, we propose TCC-aware data forwarding strategies which exploit the special characteristics of TCCs to increase the contact opportunities and then improve the performance of data forwarding. Trace-driven simulations show that our TCC-aware data forwarding strategies outperform existing data forwarding strategies in terms of data delivery ratio and network overhead.