Proactive caching for edge computing-enabled industrial mobile wireless networks

As manufacturing systems shift from automated patterns to smart frameworks such as smart factories in Industry 4.0, industrial wireless networks (IWNs) are serving as promising communication systems that can be applied to the manufacturing field. When the mobile elements and static nodes are introduced into the system, large amounts of data downloaded from mobile networks or tele-servers can be one of the greatest challenges for industrial mobile wireless networks (IMWNs). Mobility and industrial properties have rarely been considered by previous research on download strategies and caching methods. In this paper, we present a three-layer cache architecture based on edge computing and other heritage traditional networks. Then, useful spatial and temporal mobility properties are mapped using different groups and edge computing servers that contain mobile nodes. Then, according to the sojourn time, the capacity of edge computing servers and other neighbouring nodes, we propose a proactive caching strategy for large amounts of data downloaded by mobile networks that considers location and mobile trajectories. Moreover, the superiority of our proposed scheme is demonstrated by comparison case studies of widely used classical schemes. The numerical results show that our proposed strategy achieves higher goodput and real-time and other performance.