On the applicability of fair and adaptive data dissemination in traffic information systems

Abstract

Vehicular Ad hoc Networks (VANETs) are expected to serve as support to the development of not only safety applications but also information-rich applications that disseminate relevant data to vehicles. Due to the continuous collection, processing, and dissemination of data, one crucial requirement is the efficient use of the available bandwidth. Firstly, the rate of message transmissions must be properly controlled in order to limit the amount of data inserted into the network. Secondly, messages must be carefully selected to maximize the utility (benefit) gain of vehicles in the neighborhood. We argue that such selection must aim at a fair distribution of data utility, given the possible conflicting data interests among vehicles.In this work, we propose a data dissemination protocol for VANETs that distributes data utility fairly over vehicles while adaptively controlling the network load. The protocol relies only on local knowledge to achieve fairness with concepts of Nash Bargaining from game theory. We show the applicability of the protocol by giving example of utility functions for two Traffic Information Systems (TIS) applications: (i) parking-related and (ii) traffic information applications. The protocol is validated with both real-world experiments and simulations of realistic large-scale networks. The results show that our protocol presents a higher fairness index and yet it maintains a high level of bandwidth utilization efficiency compared to other approaches.