Towards Real-Time and Temporal Information Services in Vehicular Networks via Multi-Objective Optimization

Real-time and temporal information services are intrinsic characteristics in vehicular networks, where the timeliness of data dissemination and the maintenance of data quality interplay with each other and influence overall system performance. In this work, we present the system architecture where multiple road side units (RSUs) are cooperated to provide information services, and the vehicles can upload up-to-date information to RSUs via vehicle-to-infrastructure (V2I) communication. On this basis, we formulate the distributed temporal data management (DTDM) problem as a two-objective problem, which aims to enhance overall system performance on both the service quality and the service ratio simultaneously. Further, we propose a multiobjective evolutionary algorithm called MO-DTDM to obtain a set of pareto solutions and analyze how to fulfill given requirements on system performance with obtained pareto solutions. Finally, we build the simulation model and give a comprehensive performance evaluation, which demonstrates the superiority of the proposed optimization method.