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

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.