R-DRA: a replication-based distributed randomized algorithm for data dissemination in connected vehicular networks

Abstract

As data dissemination is of great importance for applications in connected vehicular networks (VANETs), we aim to facilitate the performance of data dissemination in this study. Consider strongly connected VANETs where a set of vehicular nodes exists to disseminate information. To reduce redundant transmissions and improve data dissemination delay, the number of data replicas that can be spread in the network is controlled. A replication-based distributed randomized algorithm is proposed, in which a balanced network status can be achieved after average operations among the nodes. In the algorithm, the data carrier distributes the dissemination tasks to multiple nodes to speed up the dissemination process such that the dissemination would be accelerated and consume less network resource. We evaluate the complexity of network convergence by analyzing the number of communication stages consumed when the network converges to a consensus. Theoretical analysis shows that the network can achieve balance quickly in the case of complete graph, which supports the real-time data dissemination in dense VANETs. Simulation results validate that the proposed algorithm can disseminate data to the vehicles within a specific area with high efficiency.