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Efficient On-Demand Data Service Delivery to High-Speed Trains in Cellular/Infostation Integrated Networks

机译:向蜂窝/信息站集成网络中的高速列车提供高效的按需数据服务交付

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摘要

In this paper, we investigate on-demand data services for high-speed trains via a cellular/infostation integrated network. Service requests and acknowledgements are sent through the cellular network to a content server, while data delivery is achieved via trackside infostations. The optimal resource allocation problem is formulated by taking account of the intermittent network connectivity and multi-service demands. In order to achieve efficient resource allocation with low computational complexity, the original problem is transformed into a single-machine preemptive scheduling problem based on a time-capacity mapping. As the service demands are not known a priori, an online resource allocation algorithm based on Smith ratio and exponential capacity is proposed. The performance bound of the online algorithm is characterized based on the theory of sequencing and scheduling. If the link from the backbone network to an infostation is a bottleneck, a service pre-downloading algorithm is also proposed to facilitate the resource allocation. The performance of the proposed algorithms is evaluated based on a real high-speed train schedule. Compared with the existing approaches, our proposed algorithms can significantly improve the quality of on-demand data service provisioning over the trip of a train.
机译:在本文中,我们通过蜂窝/信息站集成网络研究了高速列车的按需数据服务。服务请求和确认通过蜂窝网络发送到内容服务器,而数据传输是通过轨道边的信息站实现的。通过考虑间歇性网络连接和多服务需求来制定最佳资源分配问题。为了以低计算复杂度实现有效的资源分配,基于时间容量映射,将原始问题转换为单机抢占式调度问题。由于先验服务需求未知,提出了一种基于史密斯比率和指数容量的在线资源分配算法。基于排序和调度的理论来表征在线算法的性能界限。如果从骨干网到信息站的链接是瓶颈,则还提出了一种服务预下载算法,以促进资源分配。基于实际的高速列车时刻表评估了所提出算法的性能。与现有方法相比,我们提出的算法可以在火车行程中显着提高按需数据服务供应的质量。

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