UMUcast: A Framework for Massive Small-Data Delivering in Industrial Internet of Things

Abstract

As a key infrastructure of Industry 4.0, Industrial Internet-of-Things (IIoT) promises the opportunity to build powerful industrial environments by leveraging the growing ubiquity of wired and wireless communication technologies. Designing a data delivery scheme in the future IIoT networks is undoubtedly a challenging task, as it should satisfy several conflicting requirements: massive-scale, data-intensive, and mission-critical, the requirements of which have motivated the desired need for feasible IIoT network architecture. In particular, the traffic characteristics of certain IIoT applications feature small-data patterns especially in typical automation control scenarios such as robot control on the downlink. In order to reduce the huge overhead associated with each individual unicast transmission of the small-data message, we propose a novel “multipoint-to-multipoint” and/or “point-to-multipoint with different contents” communication paradigm-Uni-Multi-Unicast (UMUcast), which is based-on traditional 4G technologies such as evolved Multimedia Broadcast Multicast Service (eMBMS) and Group Communication System Enablers (GCSE), and novel 5G technologies such as Multi-Access Edge Computing (MEC). For the downlink, the UMUcast transmitter can jointly encode multiple-sources' small-data messages into a single chunk at MEC equipment in conjoint with a gNB, where chunk can be one-off transmission to multiple receivers simultaneously through an eMBMS frame, whereas the chunk is decoded into multiple small-data by each individual IIoT devices separately and respectively. The simulation results show that UMUcast has remarkable improvements over conventional point-to-point unicasting in handling multi-source, multi-destination, and massive small-data delivery with characteristics of low-overhead, high-throughput, and ultra-low-latency for future 5G-based IIoT networks.