A Bio-Inspired Reward-Based Message Forwarding For Vehicular Social Network

Abstract

The Ants capability of working together and their way of message transmission makes us inspired especially their cooperation for their common goal and dropping down pheromones which used as a trail for themselves and for others. We would use Ants broadcasting method for drivers‟ cooperation and message forwarding. Therefore if there were any driver who couldn‟t broadcast any emergency message related to car accident like Ants done to locate the food source, could be considered as a selfish node and couldn‟t be rewarded as cooperatives do. The previous vehicle to vehicle communication or message forwarding schemes that was tried to motivate cooperative drivers used incentive methods in which it is not motivating all participant nodes and some of them used punishment methods. These types of methods are not effective to stimulate selfish drivers. We conducted the research using embedded traffic simulation in which it includes mobility and network simulation capabilities merged together and served as multi-functional software. From the tools falling into the embedded category is National Chiao Tung University network simulator (NCTUns) which provides a full range of network stack simulation tools. Watchdog was our selfishness detection method, in which the RSU controls whether nodes are cooperative or not because the (Road Side Unit) RSU knows where the nodes were located and in which path they are drive and what messages they broadcasted. The rewarding model we used is paying per packet. The payment principle is for each successfully transmitted unit-sized packet, each of N intermediate nodes should receive λ credits, whereas the service provider (SP) would pay λ ∗ N in total. The proposed solution was evaluated by the three performance metrics which are dropped packets, selfishness detection method and delivery ratio. Based on our experiments result the number of accident increased as the number of total nodes increased in the same simulation area. As the number of nodes participated on the area increases the probability of having an accident increases and the probability of stimulating selfish nodes increased using the same incentive method and amount because there is a probability of accident commit increases and the rewarding and acknowledgement messages also increases in which it can stimulate the selfish nodes.