基于网络效用最大化理论的分布式车联网拥塞控制策略

Distributed congestion control strategy using network utility maximization theory in VANET

协同车辆安全系统依靠周期性广播的单跳数据分组来追踪周围车辆,车辆密度过高会导致信道拥塞,严重影响协同车辆安全系统的性能。现有的拥塞控制策略仅保证网络层的性能,没有考虑车辆不同交通场景下的微观服务需求。为解决该问题,提出了一种基于网络效用最大化理论的分布式拥塞控制策略。该策略首先提出了车联网信道资源分配的网络效用最大化模型,并且提出了反映车辆安全需求的效用函数;然后基于该模型,建立了传输功率固定条件下无线信道资源分配的优化问题;最后为求解该优化问题,设计了分布式拥塞控制算法UBRCC,该算法通过更新车辆的拥塞"价格"求解最优数据分组发送速率,实现了面向单个车辆安全需求的信道资源分配。仿真实验结果表明,UBRCC算法在控制信道拥塞的同时,能够有效地减小传输时延,确保数据分组可靠发送,满足车辆安全应用的服务需求。

Cooperative vehicle safety system(CVSS)rely on periodical beacons to track neighboring vehicles.High traffic density often causes channel congestion,seriously damaging the performance of CVSS.Existing congestion control strategies aim to ensure the performance in network layer,without considering the service requirements of vehicles in different driving contexts.To solve the problem,a distributed congestion control strategy using network utility maximization(NUM)theory was proposed.First of all,the NUM model for channel resource allocation was introduced.A utility function reflecting vehicle’s safety requirements was proposed in the model.Then under the condition of fixed transmit powers,a optimization problem of channel resource allocation was proposed.Lastly,to solve the optimization problem,a distributed congestion control algorithm named utility-based rate congestion control(UBRCC)algorithm was designed,the algorithm worked out the optimal beaconing rate by updating vehicle’s congestion price,realizing the resource allocation according to vehicle’s safety requirements.Simulation results validate that UBRCC algorithm can efficiently control channel congestion,reduce transmission delay,ensure reliable data transmission and satisfies the requirements of safety applications.