Injection Time Planning: Making CQF Practical in Time-Sensitive Networking
Jinli Yan, Wei Quan, Xuyan Jiang, Zhigang Sun
Abstract
Time-Aware Shaper (TAS) is a core mechanism to guarantee the deterministic transmission for periodic time-sensitive flows in Time-Sensitive Networking (TSN). The generic TAS requires complex configurations for the Gate Control List (GCL) attached to each queue in a switch. To simplify the design of a TSN switch, a Ping-Pong queue-based model named Cyclic Queuing and Forwarding (CQF) was proposed in IEEE 802.1 Qch by assigning fixed configurations to TAS. However, IEEE 802.1 Qch only defines the queue model and workflow of CQF. A global planning mechanism which maps the time-sensitive flows onto the underlying resources both temporally and spatially is urgently needed to make CQF practical.In this paper, we propose an Injection Time Planning (ITP) mechanism to optimize the network throughput of time-sensitive flows based on the observation that the start time when the packets are injected into the network has an important influence on the utilization of CQF queue resources. ITP provides a global temporal and spatial resource abstraction to make the implementation details transparent to algorithm designers. Based on our ITP mechanism, a novel heuristic algorithm named Tabu-ITP with domain-specific optimizing strategies is designed and evaluated under three typical network topologies in industrial control scenarios. Compared with the Naive algorithm without using ITP mechanism, experimental results demonstrate that Tabu-ITP improves the mapped flow number by 10x and the resource utilization by 65%.
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Cited by top-tier papers3
- DeepScheduler: Enabling Flow-Aware Scheduling in Time-Sensitive NetworkingXiaowu He, Xiangwen Zhuge, Fan Dang, Wang Xu et al.INFOCOM 2023 · 77 citations
- CaaS: Enabling Control-as-a-Service for Time-Sensitive NetworkingZheng Yang, Yi Zhao, Fan Dang, Xiaowu He et al.INFOCOM 2023 · 25 citations
- InNetScheduler: In-network scheduling for time- and event-triggered critical traffic in TSNXiangwen Zhuge, Xinjun Cai, Xiaowu He, Zeyu Wang et al.INFOCOM 2024 · 21 citations
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