Temporal Data Dissemination in Vehicular Cyber-Physical Systems

Efficient data dissemination is one of the fundamental requirements to enable emerging applications in vehicular cyber-physical systems. In this paper, we present the first study on real-time data services via roadside-to-vehicle communication by considering both the time constraint of data dissemination and the freshness of data items. Passing vehicles can submit their requests to the server, and the server disseminates data items accordingly to serve the vehicles within its coverage. Data items maintained in the database are periodically updated to keep the information up-to-date. We present the system model and analyze challenges on data dissemination by considering both application requirements and communication characteristics. On this basis, we formulate the temporal data dissemination (TDD) problem by introducing the snapshot consistency requirement on serving real-time requests for temporal data items. We prove that TDD is NP-hard by constructing a polynomial-time reduction from the Clique problem. Based on the analysis of the time bound on serving requests, we propose a heuristic scheduling algorithm, which considers the request characteristics of productivity, status, and urgency in scheduling. An extensive performance evaluation demonstrates that the proposed algorithm is able to effectively exploit the broadcast effect, improve the bandwidth efficiency, and enhance the request service chance. © 2000-2011 IEEE.

Quality-of-Experience-Oriented Autonomous Intersection Control in Vehicular Networks

Recent advances in autonomous vehicles and vehicular communications are envisioned to enable novel approaches to managing and controlling traffic intersections. In particular, with intersection controller units (ICUs), passing vehicles can be instructed to cross the intersection safely without traffic signals. Previous efforts on autonomous intersection control mainly focused on guaranteeing the safe passage of vehicles and improving intersection throughput, without considering the quality of the travel experience from the passengers' perspective. In this paper, we aim to design an enhanced autonomous intersection control mechanism, which not only ensures vehicle safety and enhances traffic efficiency but also cares about the travel experience of passengers. In particular, we design the metric of smoothness to quantitatively capture the quality of experience. In addition, we consider the travel time of individual vehicles when passing the intersection in scheduling to avoid a long delay of some vehicles, which not only helps with improving intersection throughput but also enhances the system's fairness. With the above considerations, we formulate the intersection control model and transform it into a convex optimization problem. On this basis, we propose a new algorithm to achieve an optimal solution with low overhead. Finally, we build the simulation model and implement the algorithm for performance evaluation. Comprehensive simulation results demonstrate the superiority of the proposed algorithm. © 2015 IEEE.