A Mixed Time/Event-Triggered Flow Transmission Strategy for Industrial Wireless Networks

Industrial wireless networks (IWNs) provide an efficient and flexible communication solution for smart factories. In IWNs, there are two types of data flows: time-triggered (TT) flow and event-triggered (ET) flow. Existing studies primarily focused on the scheduling of TT flow, but ignored the mixed transmission of TT flow and ET flow, and lacked the theoretical analysis for the delay of ET flow. To overcome this problem, we first establish the first-order logic constraints model for TT flow to achieve conflict-free transmission and quantify the differences in the scheduling results of TT flow across different scheduling domains from a delay perspective. We then introduce the concept of the slot load ratio (SLR) and propose the TT-driven transmission strategy for ET flow. Moreover, the average delay of ET flow is theoretically derived through the discrete Markov modeling. To evaluate the effectiveness of the proposed transmission strategy, we employ satisfiability modulo theories (SMTs), Gurobi, and deep Q-network (DQN) to verify the scheduling of the designed constraint model and analyze its schedulability for IWNs of different scales, we also experimentally discuss the impact of different network parameters on the delay of ET flow.