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Packet Scheduling for On-Demand Data Services to High-Speed Trains over Wireless Links

机译:通过无线链路的高速列车按需数据服务的数据包调度

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In this paper, we consider a cellular/infostation integrated network which supports on-demand data service delivery over a wireless link to users in a high-speed train. For the requests with different lifetimes and prices that they are willing to pay, we develop the optimal packet schedule that aims at earning the maximum revenue. To this end, we formulate the problem as an integer linear program (ILP) which is in general NP-hard. However, by exploring the special structure of the formulated ILP, we show that this problem can be turned into a P problem that admits efficient solvers. Specifically, we propose a novel Checker algorithm and prove that this algorithm is guaranteed to find the offline optimal schedule for the intended problem in polynomial time, when the number of total requests is proportional to the length of the total transmission time span. Based on the relevant insights, a class of efficient online Checker algorithms are then developed to approach the optimal schedule when a-priori knowledge of service demands and/or wireless channel capacities is not available in practical systems. It is shown that these online algorithms have a competitive ratio of 1/2, i.e., total revenue earned by them is at least half as much as the revenue earned by offline optimal schedule. Simulation results are provided to demonstrate the merit of the proposed algorithms.
机译:在本文中,我们考虑一个蜂窝/侵入综合网络,其支持在高速列车中的无线链路上的按需数据服务传送。对于具有不同寿命和价格的要求,他们愿意支付,我们开发了旨在获得最大收入的最佳数据包计划。为此,我们将问题作为整数线性程序(ILP)制定,这是一般的NP-Hard。然而,通过探索配制的ILP的特殊结构,我们表明,这个问题可以变成一个承认有效求解器的P个问题。具体地,我们提出了一种新的检查器算法,并证明该算法保证在多项式时间中找到预期问题的离线最佳时间表,当总要求的总量与总传输时间跨度的长度成比例。基于相关见解,然后开发了一类高效的在线检查算法,以在实际系统中不可用的服务需求和/或无线信道容量的优先知识时接近最佳时间表。结果表明,这些在线算法具有1/2的竞争比例,即,它们所赚取的总收入至少为下划线最佳日程所赚取的收入至少一半。提供了仿真结果以证明所提出的算法的优点。

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