Temporal Data Uploading and Dissemination in Real-Time Vehicular Networks

Temporal information services are critical in implementing emerging ITSs. Nevertheless, it is challenging to realize timely temporal data update and dissemination due to intermittent wireless connection and limited communication bandwidth in dynamic vehicular networks. To enhance system scalability, it is imperative to exploit the synergic effect of I2V and V2V communications for providing efficient temporal data disseminations in such an environment. With above motivations, we propose a novel system architecture to enable efficient data scheduling in hybrid I2V/V2V communications by having the global knowledge of network resources of the system. On this basis, we formulate a Temporal Data Upload and Dissemination (TDUD) problem, aiming at optimizing two conflict objectives, namely, the data quality and the delivery ratio, simultaneously. Furthermore, we propose an evolutionary multi-objective algorithm called MO-TDUD, which consists of a decomposition scheme for handling multiple objectives, a scalable chromosome representation for TDUD solution encoding, and an evolutionary operator designed for TDUD solution reproduction. The proposed MO-TDUD can be adaptive to different requirements on data quality and delivery ratio by selecting the best solution from the derived pareto solutions. Last but not least, we build the simulation model and implement MO-TDUD for performance evaluation. The comprehensive simulation results demonstrate the superiority of the proposed solution.