Directional Link Scheduling for Real-Time Data Processing in Smart Manufacturing System

Abstract

Internet of Things (IoT) technology has accelerated various industries through digital transformation. In an edge computing-based smart factory, a significant number of IoT devices generate large volumes of real-time data. This big data requires efficient routing among edge gateways (EGs) and an edge server for real-time data processing. Existing industrial wireless communication systems provide relatively low data rates and network capacity for real-time sensor data and control information over a wireless channel. This calls for the use of the very large bandwidth available at the mmWave spectrum for real-time data transmission. Existing data routing techniques for the mmWave band are based on traditional mobile ad hoc routing techniques and do not reduce the transmission delay for real-time sensory data in smart manufacturing systems. Therefore, to alleviate the real-time data processing requirement, we propose a new directional routing and link scheduling algorithm based on maximum weight independent set (MWIS). The proposed algorithm solves complicated MWIS problems efficiently and computes backhaul link scheduling results in a relatively short time by lowering the deafness problem among EGs. For transmission fairness, we used a Jain's fairness index method with numerical analysis of the transmission fairness constraint. We measured the efficiency of our proposed scheme in terms of throughput, delay, packet loss rate, and transmission fairness. Our simulation results show that the proposed scheme outperforms existing mmWave routing techniques. Moreover, we investigated the performance difference between the proposed algorithm and the optimal solution.