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Top-k Publish/Subscribe for Ride Hitching

机译:Top-k发布/订阅乘坐搭便车

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With the continued proliferation of mobile Internet and geo-locating technologies, carpooling as a green transport mode is widely accepted and becoming tremendously popular worldwide. In this paper, we focus on a popular carpooling service called ride hitching, which is typically implemented using a publish/subscribe approach. In a ride hitching service, drivers subscribe the ride orders published by riders and continuously receive the matching ride orders until one is picked. The current systems (e.g., Didi Hitch) adopt a threshold-based approach to filter ride orders. That is, a new ride order will be sent to all subscribing drivers whose planned trips can match the ride order within a pre-defined detour threshold. A limitation of this approach is that it is difficult for drivers to specify a reasonable detour threshold in practice. In addressing this problem, we propose a novel type of top-k subscription queries called Top-k Ride Subscription (TkRS) query, which continuously returns to drivers the best k ride orders that match their trip plans. We propose two efficient algorithms to enable the top-k result maintenance. Finally, extensive experiments on real-life datasets suggest that our proposed algorithms are capable of achieving desirable performance in practical settings.
机译:随着移动互联网和地理定位技术的持续扩散,作为绿色传输模式的拼车被广泛接受,并在全球范围内变得非常流行。在本文中,我们专注于称为Ride Hectring的流行拼车服务,通常使用发布/订阅方法来实现。在乘坐搭便车服务中,司机订阅了骑手发布的骑行订单,并连续收到匹配的骑行订单,直到挑选。当前系统(例如,DIDI Hitch)采用基于阈值的方法来过滤骑行命令。也就是说,将发送新的乘坐订单,其计划旅行可以在预定义的绕行阈值中匹配乘坐速度顺序的所有订阅驱动程序。对这种方法的限制是驾驶员难以在实践中指定合理的绕行阈值。在解决此问题时,我们提出了一种名为Top-K Ride订阅(TKRS)查询的新型TOP-K订阅查询,该查询持续返回驾驶员符合其旅行计划的最佳K乘坐订单。我们提出了两个有效的算法来实现Top-K结果维护。最后,对现实生活数据集的广泛实验表明,我们所提出的算法能够在实际设置中实现所需的性能。

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