车辆雾计算中基于反向拍卖的停车辅助方案

Parking Assistance Scheme Based on Reverse Auction in Vehicle Fog Computing

车辆雾计算(VFC)作为雾计算的一种扩展模式,将雾计算与传统的车载网络相结合,为车辆用户提供实时响应服务。停车辅助与VFC相结合可以帮助车辆获取停车信息资源,改善交通拥堵状况,但车辆用户及时高效地获取停车信息成为VFC停车辅助中急需解决的问题。为此,构建一种VFC停车辅助系统模型,在该模型的基础上提出一种基于反向拍卖的VFC停车辅助分配策略RAFC,以激励车辆用户和雾节点以拍卖的方式积极参与资源分配并获取收益。理论分析和实验结果表明,RAFC策略可以实现个人理性和预算平衡,相比随机匹配法,其能提高匹配成功率与社会效用并降低用户的开销成本。

Vehicle Fog Computing(VFC)is an extended model of fog computing that combines fog computing with traditional in-vehicle networks to provide real-time response services for vehicle users.The combination of intelligent parking assistance and VFC can help vehicles obtain parking information resources and improve traffic conditions.However,how to enable vehicle users to efficiently obtain parking information remains to be an issue to be solved in VFC parking assistance.Therefore,this paper establishes a VFC parking assistance system model,and on this basis proposes a VFC parking assistance allocation strategy,RAFC,which uses reverse auction to encourage vehicle users and fog nodes to actively participate in resource allocation to obtain revenue.Theoretical analysis and experimental results show that the RAFC strategy can achieve a balance between personal rationality and budge.Compared with the random matching method,RAFC can improve the matching success rate and social utility while reducing the overhead for users.