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In feed-forward time-sensitive networks with Deficit Round-Robin (DRR),worst-case delay bounds were obtained by combining Total Flow Analysis (TFA)with the strict service curve characterization of DRR by Tabatabaee et al. Thelatter is the best-known single server analysis of DRR, however the former isdominated by Polynomial-size Linear Programming (PLP), which improves the TFAbounds and stability region, but was never applied to DRR networks. We firstperform the necessary adaptation of PLP to DRR by computing burstiness boundsper-class and per-output aggregate and by enabling PLP to support non-convexservice curves. Second, we extend the methodology to support networks withcyclic dependencies: This raises further dependency loops, as, on one hand, DRRstrict service curves rely on traffic characteristics inside the network, whichcomes as output of the network analysis, and on the other hand, TFA or PLPrequires prior knowledge of the DRR service curves. This can be solved byiterative methods, however PLP itself requires making cuts, which imposes otherlevels of iteration, and it is not clear how to combine them. We propose ageneric method, called PLP-DRR, for combining all the iterations sequentiallyor in parallel. We show that the obtained bounds are always valid even beforeconvergence; furthermore, at convergence, the bounds are the same regardless ofhow the iterations are combined. This provides the best-known worst-case boundsfor time-sensitive networks, with general topology, with DRR. We apply themethod to an industrial network, where we find significant improvementscompared to the state-of-the-art.

Worst-case Delay Analysis of Time-Sensitive Networks with Deficit Round-Robin