Social acquaintance based routing in Vehicular Social Networks

摘要

The concept of Internet of Things (IoT) provides us the opportunity to interconnect different objects with the communication and processing capabilities for a diverse range of applications. Recently, Vehicular Social Networks (VSNs) have been introduced through the combination of relevant concepts from two primary disciplines, i.e., social networks and Vehicular Ad hoc Networks (VANETs). Inspired from the social acquaintance in our daily life, we present a Social Acquaintance based Routing Protocol (SARP) for VSNs, which collectively consider three social feature metrics to make a forwarding decision. Proposed protocol aims to reduce End-to-End delay and improve packet delivery ratio in VSNs. Additionally, SARP overcomes the shortcoming of topology based routing and optimum local situation of geographically based routing protocols by considering the global and local community acquaintance of nodes. We performed extensive simulations under constant node density with different mobility speed and constant speed with varying node density to study the effect of node mobility speed and density on end-to-end delay and packet delivery ratio. The simulation results show that SARP outperforms GPSR by 22% and 26% in terms of end-to-end delay and packet delivery ratio respectively. Also, SARP outperforms AOVD in terms of end-to-end delay. (C) 2017 Elsevier B.V. All rights reserved.