Scalable No-wait Scheduling with Flow-aware Model Conversion in Time-Sensitive Networking

Zhang, Yanzhou; Xu, Qimin; Wang, Shouliang; Chen, Yingxiu; Xu, Lei; Chen, Cailian

doi:10.1109/globecom48099.2022.10001004

Cited by 9 publications

(1 citation statement)

References 11 publications

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“…1) Sorting Strategy Comparison: In incremental scheduling of the HFG method for each partition, different flow orders are compared to filter the optimal sorting strategy, including the random, down or up order by flow period, frame length and offset bound [21], respectively. As shown in Fig.…”

Section: B Simulation Resultsmentioning

confidence: 99%

Efficient Flow Scheduling for Industrial Time-Sensitive Networking: A Divisibility Theory-Based Method

Zhang

et al. 2022

IEEE Trans. Ind. Inf.

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Industrial Time-Sensitive Networking (TSN) provides deterministic mechanisms for real-time and reliable flow transmission. Increasing attention has been paid to efficient scheduling for time-sensitive flows with stringent requirements such as ultra-low latency and jitter. In TSN, the fine-grained traffic shaping protocol, cyclic queuing and forwarding (CQF), eliminates uncertain delay and frame loss by cyclic traffic forwarding and queuing. However, it inevitably causes high scheduling complexity. Moreover, complexity is quite sensitive to flow attributes and network scale. The problem stems in part from the lack of an attribute mining mechanism in existing frame-based scheduling. For time-critical industrial networks with large-scale complex flows, a so-called hyper-flow graph based scheduling scheme is proposed to improve the scheduling scalability in terms of schedulability, scheduling efficiency and latency & jitter. The hyper-flow graph is built by aggregating similar flow sets as hyper-flow nodes and designing a hierarchical scheduling framework. The flow attribute-sensitive scheduling information is embedded into the condensed maximal cliques, and reverse maps them precisely to congestion flow portions for rescheduling. Its parallel scheduling reduces network scale induced complexity. Further, this scheme is designed in its entirety as a comprehensive scheduling algorithm GH 2 . It improves the three criteria of scalability along a Pareto front. Extensive simulation studies demonstrate its superiority. Notably, GH 2 is verified its scheduling stability with a runtime of less than 100 ms for 1000 flows and near 1/430 of the SOTA FITS method for 2000 flows.

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Section: B Simulation Resultsmentioning

confidence: 99%

Efficient Flow Scheduling for Industrial Time-Sensitive Networking: A Divisibility Theory-Based Method

Zhang

et al. 2022

IEEE Trans. Ind. Inf.

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Enhanced conflict‐aware iterated integer linear programming for IEEE 802.1Qbv Time‐Sensitive Network scheduling

Kerem Özkan,

Cevher

2024

Int J Communication

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SummaryDeterministic communication plays a crucial role for real‐time distributed embedded systems by guaranteeing a low end‐to‐end delay and minimal jitter. Conflict‐aware iterated ILP‐based scheduling (IIS) is an incremental approach to enhance the scalability of single‐shot ILP computation to solve the computationally hard Qbv‐compliant offline scheduling problem for IEEE 802.1 Time‐Sensitive Networking (TSN). Taking into account the conflicting demands of the streams, IIS computes no‐wait schedules by dividing the set of streams into disjoint partitions, each of which is incrementally scheduled by an ILP solver. In this work, defining the no‐wait communication constraints for TSN scheduling, we propose a novel iterated scheduling approach, namely, O‐IIS, with a backtracking mechanism and partial solution support extending the conventional IIS procedure. O‐IIS relies on an ordering strategy to determine the order in which the constructed partitions will be processed by an ILP solver. We evaluate the performance of our approach in terms of schedulability success rate and schedule synthesis time using various network topologies and different partitioning schemes to construct the partitions. The evaluation results show that our approach provides significantly better scheduling performance compared to the existing work in the literature.

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A Survey of Scheduling Algorithms for the Time-Aware Shaper in Time-Sensitive Networking (TSN)

et al. 2023

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Scalable No-wait Scheduling with Flow-aware Model Conversion in Time-Sensitive Networking

Cited by 9 publications

References 11 publications

Efficient Flow Scheduling for Industrial Time-Sensitive Networking: A Divisibility Theory-Based Method

Efficient Flow Scheduling for Industrial Time-Sensitive Networking: A Divisibility Theory-Based Method

Enhanced conflict‐aware iterated integer linear programming for IEEE 802.1Qbv Time‐Sensitive Network scheduling

A Survey of Scheduling Algorithms for the Time-Aware Shaper in Time-Sensitive Networking (TSN)

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