出租车的GPS轨迹数据在发展智慧交通方面有很大的潜力.通过分析这些数据可以发现车辆之间存在的社会关系或属性,而这些发掘出来的信息对于设计出性能更优的VANETs路由算法可以进行更好的指导.通过对GPS轨迹数据进行分析,获得了车辆节点的中心性和偏好活动区域;依据节点的这些属性,设计了基于中心性的路由和基于偏好性的路由,并进一步设计了同时考虑两者的路由,即TDSAR(Trace Data's Social Attribute Routing,基于真实轨迹社会属性的路由);最后借助ONE作为平台,模拟路由算法并对算法的性能进行了评价.实验结果表明,在测试场景下,TDSAR算法可以在保持较小开销并保证传输延时不提高的前提下,获得较高的投递成功率.通过深入的挖掘车辆间的社会关系,有助于更好地选择中继节点,从而促进VANETs的发展.%The GPS trace data for taxi has great potential in the development of intelligent transportation. By analysis of the data,the social relations or attributes between vehicles can be found,which could play a guiding role in design of VANETs routing with greater perform-ance. The vehicle nodes' centricity and preference are obtained through analysis of the GPS trace data,and based on these properties,the routing algorithms are designed based on both centricity and preference,as well as both of them,which is named TDSAR( Trace Data' s Social Attribute Routing) . Finally,with the ONE as the platform,the routing algorithm is simulated and its performance is evaluated. The results show that TDASR could get high delivery ratio on the premise of lower occupancy and stable delay. Through the in-depth mining of the vehicular relationships,the VANETs could get a better development when the better relay nodes are chosen.
展开▼
