Joint Connection Modes, Uplink Paths and Computational Tasks Assignment for Unmanned Mining Vehicles' Energy Saving in Mobile Edge Computing Networks

At present, most unmanned mining vehicles (UMVs) adopt batteries to meet the requirements of low power consumption in driving control systems, and saving energy is the key to increase the working time and production efficiency. Mobile edge computing (MEC) is an effective technology that can improve the driving performance, whereas reduces the power consumption caused by the UMV's CPU. However, sending more offloading tasks to MEC servers means higher wireless channel transmission power, and especially in mining areas, where the communication quality of wireless channels are easily deteriorated by dust, rocks and ravines. To solve this contradiction, this article firstly analyzes the UMVs' consumption of computational power and communicational power based on the proposed MEC architecture. Then, considering that flexible connection methods can reduce the end-to-end delay of offloading tasks and improve the use efficiency of link resources, a joint connection modes, uplink paths and computational tasks assignment method is proposed to reduce the power consumption under a strict delay constraint. Furthermore, a novel algorithm is presented to obtain the optimal parameters. Finally, through a simulation experiment, the effectiveness of this method in reducing the power consumption compared with the shortest path method is proved.