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Proactive caching for edge computing-enabled industrial mobile wireless networks

机译:主动缓存支持基于边缘计算的工业移动无线网络

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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.
机译:随着制造系统从自动化模式转变为诸如工业4.0中的智能工厂之类的智能框架,工业无线网络(IWN)成为可以应用于制造领域的有希望的通信系统。当将移动元素和静态节点引入系统时,从移动网络或远程服务器下载的大量数据可能是工业移动无线网络(IMWN)面临的最大挑战之一。关于下载策略和缓存方法的先前研究很少考虑移动性和工业属性。在本文中,我们提出了一种基于边缘计算和其他传统传统网络的三层缓存体系结构。然后,使用不同的组和包含移动节点的边缘计算服务器来映射有用的空间和时间移动性属性。然后,根据逗留时间,边缘计算服务器和其他相邻节点的容量,我们为考虑位置和移动轨迹的移动网络下载的大量数据提出了一种主动缓存策略。此外,通过广泛使用的经典方案的比较案例研究证明了我们提出的方案的优越性。数值结果表明,本文提出的策略具有较高的吞吐量和实时性等性能。

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