Stochastic Network Calculus Analysis of SPMA for Delay-Sensitive Industrial IoT Networks

The Statistical Priority-based Multiple Access (SPMA) protocol is particularly well-suited for accommodating massive concurrent access and fulfilling differentiated traffic priority requirements in large-scale industrial scenarios. However, existing performance analyses of SPMA have long focused on packet loss rate and throughput, lacking systematic research on its delay characteristics. This paper conducts a Stochastic Network Calculus (SNC) analysis of SPMA, filling the gap in the theoretical analysis of its delay performance for mission-critical industrial applications. First, a homogeneous Poisson point process is used to model the network topology, and techniques such as binary exponential backoff and time-frequency hopping are incorporated to analyze the burst success probability of SPMA. Second, based on the moment generating function-based SNC theory (MGF-SNC), a numerical upper bound of the statistical delay violation probability (SDVP) is derived, and a delay minimization model is constructed. Finally, the impact of key parameters on the delay performance of SPMA networks is analyzed. Experimental results validate the effectiveness of the proposed scheme, demonstrating that a tight SDVP upper bound can be obtained, providing theoretical support for optimizing deterministic latency in next-generation IIoT networks.