Abstract
Edge computing technology emerges as a novel computing paradigm that makes use of resources closed to the devices of smart rail system. However, it is difficult to support data offloading to the stations directly from different trains, due to the limited coverage of the stations equipped with MEC servers. Therefore, multi-hop ad hoc network is considered and introduced in this case. In this article, we propose an improved optimization framework for MEC-enabled smart rail system by multi hop data communication and blockchain technology. The tasks can be offloaded to the MEC servers through multi-hop transmission between trains, even requesting trains are not covered by servers. Moreover, blockchain technology is utilized to ensure the security and reliability of the data during multi-hop transmission. Then the offloading routing path and offloading strategy are co-optimized to minimize both delay and cost of the system. We formulate the proposed optimization problem as a Markov decision process (MDP), and adopt deep reinforcement learning (DRL) to solve it. Simulation results show that the proposed scheme can improve system performance significantly compared with other existing schemes.
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