Data Packet Schedule Algorithm For High Speed Train's WIFI Dynamic Information Transmission

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. 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 frame-miniframe mapping. The optimal resource allocation problem is formulated by taking account of the intermittent network connectivity and multi-service demands.In former works, the price of each data packer that request willing to pay is constant during the lifetime of the request. But under some circumstance, the price should be a function of time, changing with time past. We set the price to be a two partition function in this paper, in the former half period lifetime of request is full, and half in the last lifetime. And we formulated the new problem based on new price model, and develop a greedy data packet schedule algorithm, then we set the price function be a liner function.Further more, in former works, only single type of request exist in the system, only the completed transmission request count price and calculate the price based on the amount of transmission data packet whether the request is completed or not. In this paper, we set the both type of request generated during the trip of train, and based on this new scenario we develop a mixed algorithm.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.