Intelligent scheduling mechanism of time-sensitive network modal in polymorphic network

Sijin YANG; Lei ZHUANG; Yu SONG; Jiaxing WANG; Xinyu YANG

doi:10.11959/j.issn.1000-436x.2022078

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Intelligent scheduling mechanism of time-sensitive network modal in polymorphic network

Papers | 更新时间：2024-06-05

- Intelligent scheduling mechanism of time-sensitive network modal in polymorphic network
- Journal on Communications Vol. 43, Issue 5, Pages: 82-91(2022)
- 作者机构：
  
  1. 郑州大学计算机与人工智能学院，河南郑州 450001
  2. 郑州大学网络空间安全学院，河南郑州 450002
- 作者简介：
- 基金信息：
  
  State Grid Corporation of China Science and Technology Project(5700-202024176A-0-0-00)
- DOI：10.11959/j.issn.1000-436x.2022078
  CLC： TN92
- Online First：2022-05，
  
  Published：25 May 2022
- 稿件说明：
移动端阅览
Sijin YANG, Lei ZHUANG, Yu SONG, et al. Intelligent scheduling mechanism of time-sensitive network modal in polymorphic network[J]. Journal on Communications, 2022, 43(5): 82-91.
DOI：

Sijin YANG, Lei ZHUANG, Yu SONG, et al. Intelligent scheduling mechanism of time-sensitive network modal in polymorphic network[J]. Journal on Communications, 2022, 43(5): 82-91. DOI： 10.11959/j.issn.1000-436x.2022078.

摘要

针对多模态网络中时间敏感网络模态转发调度不确定、求解时间长等问题，提出了一种基于CSQF的时间敏感网络模态的联合路由与调度机制。综合考虑有界时延需求、网络状态和不同的路由机制，建立联合缓存队列和路由的混合资源调度模型，旨在优化整个网络的资源使用。基于深度强化学习方法，利用流量特征与缓存队列利用率来预测下一循环的缓存利用率。此外，基于多队列CSQF转发调度机制和基于缓存利用率的显式路由算法，提出了一种迭代调度算法，实现了确定性转发和资源分配。仿真结果表明，所提机制可以根据网络的资源使用情况有效地调整确定性应用的传输调度，与其他离线调度机制相比，具有更好的调度性能。

Abstract

For the problems of uncertain forwarding scheduling and long solving time of time-sensitive network modal in polymorphic network

a joint routing and scheduling mechanism of time-sensitive network modal based on CSQF was proposed.Considering the requirement of bounded delay

network state and different routing mechanisms

a hybrid resource scheduling problem of joint cache queue and routing was formulated to optimize the resource usage of the entire network.Then

the traffic characteristics and cache queue utilization was used to predict the cache utilization of the next cycle

which was based on deep reinforcement learning.In addition

by using multi-queue CSQF forwarding scheduling mechanism and explicit routing algorithm based on cache utilization

an iterative scheduling algorithm was proposed to achieve deterministic forwarding and resource allocation.Simulation results show that the mechanism can effectively adjust the transmission scheduling of deterministic applications according to the resource usage of the network

and has better schedulability compared with other off-line scheduling mechanisms.

关键词

Keywords

references

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