Opportunistic auto-adaptive dissemination in vehicular ad-hoc networks

Opportunistic dissemination is a promising research domain, for more and more applications that need efficient information spreading in one area are emerging in vehicular ad-hoc networks (VANETs). The most important characteristic of vehicular networks is that they do not have a stable framework. The communication between vehicles mostly depends on the unexpected meeting. Some available data dissemination schemes, however, fail to utilize the peculiarities of vehicular networks. In this paper we propose a novel opportunistic auto-adaptive dissemination algorithm for VANETs. This algorithm takes into account the moving directions of vehicles, and it dynamically changes the number of message replicas to control the network load. It also devises rules how to inform the entering vehicles at the regional border. We evaluate our approach and the results show that our algorithm achieves a good delivery ratio with a smaller network load compared with Random Choice algorithm and Epidemic dissemination algorithm over a series of scenarios.