On latency reductions in vehicle-to-vehicle networks by random linear network coding

Abstract

In the Internet of vehicles (IoV), direct communication between vehicles, i.e., vehicle-to-vehicle (V2V) may have lower latency, compared to the schemes with help of Road Side Unit (RSU) or base station. In this paper, the scenario where the demands of a vehicle are satisfied by cooperative transmissions from those one in front is considered. Since the topology of the vehicle network is dynamic, random linear network coding is applied in such a multi-source single-sink vehicle-to-vehicle network, where each vehicle is assumed to broadcast messages to others so that the intermediate vehicles between sources and sink can reduce the latency collaboratively. It is shown that the coding scheme can significantly reduce the time delay compared with the non-coding scheme even in the channels with high packet loss rate. In order to further optimize the coding scheme, one can increase the generation size, where the generation size means the number of raw data packets sent by the source node to the sink node in each round of communication. Under the premise of satisfying the coding validity, we can dynamically select the Galois field size according to the number of intermediate nodes. It is not surprised that the reduction in the Galois field size can further reduce the transmission latency.