Resource-Saving Customizable Pipeline Network Architecture for Multi-Signal Processing in Edge Devices

Sensors (Basel). 2022 Jul 30;22(15):5720. doi: 10.3390/s22155720.

Abstract

With the development of the information age, the importance of edge computing has been highlighted in industrial site monitoring, health management, and fault diagnosis. Among them, the processing and computing of signals in edge scenarios is the cornerstone of realizing these scenarios. While the performance of edge devices has been dramatically improved, the demand for signal processing in the edge side has also ushered in explosive growth. However, the deployment of traditional serial or parallel signal processing architectures on edge devices has problems such as poor flexibility, low efficiency, and low resource utilization, making edge devices unable to exert their maximum performance. Therefore, this paper proposes a resource-saving customizable pipeline network architecture with a space-optimized resource allocation method and a coordinate addressing method for irregular topology. This architecture significantly improves the flexibility of multi-signal processing in edge devices, improves resource utilization, and further increases the performance potential of edge devices. Finally, we designed a comparative experiment to prove that the resource-saving and customizable pipeline network architecture can significantly reduce resource consumption under the premise of meeting real-time processing requirements.

Keywords: FPGA; edge computing; pipeline network architecture; signal processing.

Grants and funding

This work was supported by the National Basic Scientific Research Program of China (Grant No. JCKY2019602B002 and No. JCKY2020204C021).