In order to provide high-quality and highly reliable video delivery services for mobile users, especially train passengers, we propose a proactive content caching scheme that uses transportation systems. In our system, we place content servers with cache capability [e.g., content centric networking/named data networking (CCN/NDN)] in every train and station. Video segments encapsulated by MPEG-Dynamic Adaptive Streaming over HTTP (MPEG-DASH) are distributed and pre-cached by the station servers before the trains arrive at the stations. The trains receive content via high-speed wireless transport, such as wireless LANs or millimeter waves, when they stop at the stations. We developed prototype systems based on hypertext transfer protocol and CCN/NDN protocol, evaluate their performance through two field experiments that uses actual trains, and compare with traditional video streaming over cellular networks. Such evaluations indicate that our system can achieve high-quality video delivery without interruption for up to 50 users simultaneously.

The architecture of a data flow machine, called DFM, is developed for parallel list processing. The DFM can maximally exploit parallelism inherent in list processing, due to its ultra-multi-processing mechanism, packet communication-based parallel and pipeline execution mechanism, and lenient cons mechanism. A practical DFM implementation is described. A DFM prototype machine is implemented and DFM performance is evaluated in a simulation on the register transfer level using several benchmark programs. The DFM single processor system is shown to be about five times faster than conventional machines which use the same device technology, while a multi-processor DFM system is shown to achieve a linear speed-up ratio of 0.6 ~ 0.9.