Abstract

Environments built from the edge-based Industrial Internet of Things (IIoT) are maelstroms of information that continuously flows between heterogeneous data objects, such as sensors and devices, and edge nodes. However, the explosive growth in the number of IIoT data objects connected to edge nodes generally results in significant computation and storage requirements, which exceed those of resource-constrained edge nodes. The problem mentioned above causes a major concern related to efficient memory usage and faster communication processing in data acquisition. Therefore, in this article, we propose a multibuffers multiobjects (MBMOs) architecture to support the parallel delivery of multiple data objects to multiple variable-length buffer blocks. Furthermore, a mathematical model is established, aiming to find the optimum buffer according to the size of each communication data packet. For the aforementioned matching problem, a spatiotemporal resource allocation algorithm is designed to maximize memory usage while minimizing communication processing time. We implement our MBMO in a monitoring system in which embedded programmable logic controllers (ePLCs) serve as the edge nodes. The analyses illustrate that memory usage and time efficiency are improved greatly with the utilization of MBMO.

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