.png){kind=icon}
返回
A time-sensitive network scheduling algorithm based on improved ant colony optimization
.png){kind=icon}
OA
AI
DOI：10.1016/j.aej.2020.06.013.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Cyber-physical system (CPS) is the core technology of Industry 4.0. The deterministic behaviors of the CPS require real-time deterministic guarantee. Therefore, this paper improves the ant colony optimization (ACO) into a scheduling algorithm for time-triggered flows in time-sensitive network (TSN), a standard developed by the IEEE 802.1 Working Group that fully satisfies the strict end-to-end delay requirements of industrial applications. Simulation results show that the improved ACO (IACO) can schedule the time-triggered flows in the TSN excellently, and outperform the traditional ACO in convergence speed, optimization ability and the proneness to local optimum trap. To sum up, this paper provides an effective real-time guarantee for the TSNs. (C) 2020 The Authors. Published by Elsevier B.V. on behalf of Faculty of Engineering, Alexandria University.
Keyword:
Cyber-physical system (CPS)
Time-sensitive network (TSN)
Scheduling algorithm
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
6.8
论文数:
6.3K
被引数:
2.6W
机构
引用论文
分享收藏The saltern-derived Paludifilum halophilum DSM 102817T is a new high-yield ectoines producer in minimal medium and under salt stress conditions.png)
3 BiotechOAAI
3 BiotechIF0
OAAI分享收藏Optimal Energy Resources Allocation Method of Wireless Sensor Networks for Intelligent Railway SystemsSENSORSOAAI
SENSORSIF3.5
OAAI分享收藏Phytochrome-mediated delay of plastid senescence in mustard cotyledons: changes in pigment contents and ultrastructurePlanta
PlantaIF0
PREAI
分享收藏
查看更多内容