Data stream scheduling algorithm based on link congestion probability optimization

Pengyi Wang

doi:10.1117/12.3011978

7 December 2023 Data stream scheduling algorithm based on link congestion probability optimization

Pengyi Wang

Proceedings Volume 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023); 1294119 (2023) https://doi.org/10.1117/12.3011978
Event: Third International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 203), 2023, Yinchuan, China

Abstract

Aiming at the problem of increased network delay due to congestion caused by link collision caused by improper traffic scheduling in the industrial Internet, this paper proposes a flow scheduling strategy based on probability-based data flow path planning within a period of time. On the basis of the software-defined network centralized control architecture, the controller collects the switches and edges’ node information in the topological network to meet the QoS of different services as much as possible while ensuring that more services are responded. In the scheduling period, the congestion probability of each link is introduced, and the relative delay is obtained by combining the delay required by the link. The optimal path under the current strategy is selected to optimize the result of data flow scheduling and reduce data flow transmission delay.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Pengyi Wang "Data stream scheduling algorithm based on link congestion probability optimization", Proc. SPIE 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023), 1294119 (7 December 2023); https://doi.org/10.1117/12.3011978

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