INBAR: A new INterest-BAsed Routing framework in vehicular social networks

In recent years, socially aware networking (SAN) has given rise to vehicular social networks (VSNs). By exploiting social properties, SAN provides a promising paradigm for data routing and forwarding. However, routing in such VSNs is challenging since it needs to handle a series of problems such as the dynamic topology, network partitioning and long delays. Recently, interest-based approaches, which try to exploit the interest information of VSN nodes to make better forwarding decisions, have attract tremendous attention in VSN routing design. In this paper, we propose a new INterest-BAsed Routing (INBAR) framework for VSNs. Inspired by general laws in molecular chemistry, we develop a new metric community energy to indicate nodes' social proximity to make forwarding decisions. Community energy is generated when two nodes encounter and it is shared by encountering nodes. The proposed INBAR framework considers community energy of encountering nodes and selects forwarders with higher community energy to the destination node or the destination community. Extensive simulations have been conducted to demonstrate that INBAR outperforms the existing algorithms including the BEEINFO, Epidemic and PRoPHET.