| Title | Towards Network-Wide Scheduling for Cyclic Traffic in IP-based Deterministic Networks |
| Publication Type | Conference Paper |
| Year of Publication | 2021 |
| Authors | Huang, Yudong, Wang, Shuo, Feng, Tao, Wang, Jiasen, Huang, Tao, Huo, Ru, Liu, Yunjie |
| Conference Name | 2021 4th International Conference on Hot Information-Centric Networking (HotICN) |
| Keywords | Collaboration, composability, compositionality, Cycle Specified Queuing and Forwarding, Deterministic Networks, Human Behavior, Information Centric Networks, Job shop scheduling, mathematical models, Metrics, Network topology, Planning, pubcrawl, reinforcement learning, resilience, Resiliency, Scalability, scheduling, Scheduling algorithms, simulation |
| Abstract | The emerging time-sensitive applications, such as industrial automation, smart grids, and telesurgery, pose strong demands for enabling large-scale IP-based deterministic networks. The IETF DetNet working group recently proposes a Cycle Specified Queuing and Forwarding (CSQF) solution. However, CSQF only specifies an underlying device-level primitive while how to achieve network-wide flow scheduling remains undefined. Previous scheduling mechanisms are mostly oriented to the context of local area networks, making them inapplicable to the cyclic traffic in wide area networks. In this paper, we design the Cycle Tags Planning (CTP) mechanism, a first mathematical model to enable network-wide scheduling for cyclic traffic in large-scale deterministic networks. Then, a novel scheduling algorithm named flow offset and cycle shift (FO-CS) is designed to compute the flows' cycle tags. The FO-CS algorithm is evaluated under long-distance network topologies in remote industrial control scenarios. Compared with the Naive algorithm without using FO-CS, simulation results demonstrate that FO-CS improves the scheduling flow number by 31.2% in few seconds. |
| DOI | 10.1109/HotICN53262.2021.9680843 |
| Citation Key | huang_towards_2021 |
Towards Network-Wide Scheduling for Cyclic Traffic in IP-based Deterministic Networks