Replication-Based Data Dissemination in Connected Internet of Vehicles

Abstract

Due to the dynamically changing topology of Internet of Vehicles (IoV), it is a challenging issue to achieve efficient data dissemination in IoV. This paper considers strongly connected IoV with a number of heterogenous vehicular nodes to disseminate information and studies distributed replication-based data dissemination algorithms to improve the performance of data dissemination. Accordingly, two data replication algorithms, a deterministic algorithm and a distributed randomised algorithm, are proposed. In the proposed algorithms, the number of message copies spread in the network is limited and the network will be balanced after a series of average operations among the nodes. The number of communication stages needed for network balance shows the complexity of network convergence as well as network convergence speed. It is proved that the network can achieve a balanced status after a finite number of communication stages. Meanwhile, the upper and lower bounds of the time complexity are derived when the distributed randomised algorithm is applied. Detailed mathematical results show that the network can be balanced quickly in complete graph; thus highly efficient data dissemination can be guaranteed in dense IoV. Simulation results present that the proposed randomised algorithm outperforms the present schemes in terms of transmissions and dissemination delay.