Mission-critical Industrial Internet of Things (IIoT) traffic flows require bounded network latency and jitter guarantees to ensure the safe functioning of critical industrial infrastructure. These flows are typically communicated via commodity network routers with conventional First-In-First-Out (FIFO) buffers. FIFO has proven to be the culprit of the well-known bufferbloat phenomenon, and the deployment of Active Queue Management (AQM) schemes have demonstrated significant performance improvements for latency-sensitive applications over the Internet in the IT domain. However, the bufferbloat phenomenon and the efficacy of AQM schemes have not been studied in IIoT-based OT domain. In this paper, we propose the use of AQM as a lightweight and non-intrusive mechanism for assisting mission-critical traffic flows in IIoT networks. Our experimental results demonstrated that multi-queue AQM schemes provide substantial flow isolation and capacity sharing benefits, and significantly improve the performance of mission-critical traffic flows under network pressure. We further provide deployment recommendations based on our experimental insights.
This paper focuses on the Low-Bitrate Secure Speech Communications based on the Structured Spectral Compression (LB-S2C2). Specifically, the Mel spectral matrix of the speech signal is first encoded at the transmitter side through compressive sensing based on waveform segmentatio…
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