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Cache-Based Popular Services Pushing on High-Speed Train by Using Converged Broadcasting and Cellular Networks

机译:通过使用融合广播和蜂窝网络推动基于高速缓存的基于缓存的流行服务

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This paper presents a cache-based popular services pushing solution on high-speed train (HST) by using converged wireless broadcasting and cellular networks. Pushing and caching popular services on the HST to improve the capacity of the network is a very efficient way; and it can also bring a better user experience. The most popular services are transmitted and cached on the vehicle relay station of the train ahead the departure time in the proposed model. Then, the most popular services are broadcasted and cached on the User Equipment after all the passengers are on the train; the less popular services are delivered to the passengers by P2P mode through the relayed cellular network on the train. Specifically, we firstly use the dynamic programming algorithm to maximize the network capacity in limited pushing time, which can be converted to the 0-1 Knapsack problem. Furthermore, we propose three greedy algorithms to approximate the optimal solution on account of the high time complexity of dynamic programming when the input scale gets bigger. And simulation results show that the proposed popularity-based greedy algorithm performs well. Moreover, as the passengers may get on and off the HST when arriving at an intermediate station, a services rebroadcast algorithm is employed when more intermediate stations are considered. U-shaped distribution is adopted to indicate the number of passengers getting on and off the train. Simulations also show that the proposed rebroadcast algorithm can efficiently improve the capacity of the converged networks.
机译:本文提出了一种使用融合的无线广播和蜂窝网络的高速列车(HST)上基于缓存的流行服务推送解决方案。在HST上推送和缓存流行的服务以提高网络容量是一种非常有效的方法。并且还可以带来更好的用户体验。在提出的模型中,最流行的服务在出发时间之前在火车的车辆中继站上传输和缓存。然后,在所有乘客上车之后,最受欢迎的服务将在用户设备上广播并缓存;不太受欢迎的服务是通过P2P模式通过火车上的中继蜂窝网络传递给乘客的。具体而言,我们首先使用动态规划算法在有限的推送时间内最大化网络容量,并将其转换为0-1背包问题。此外,由于输入规模变大时动态编程的时间复杂度高,我们提出了三种贪婪算法来逼近最优解。仿真结果表明,所提出的基于流行度的贪婪算法性能良好。此外,由于乘客到达中间站时可能上下车,因此在考虑更多中间站时采用服务转播算法。采用U形分布来指示上下火车的乘客数量。仿真还表明,所提出的重播算法可以有效地提高融合网络的容量。

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