The ubiquitous and deterministic communication systems are becoming indispensable for future vertical applications such as industrial automation systems and smart grids.5G-TSN(Time-Sensitive Networking)integrated netw...The ubiquitous and deterministic communication systems are becoming indispensable for future vertical applications such as industrial automation systems and smart grids.5G-TSN(Time-Sensitive Networking)integrated networks with the 5G system(5GS)as a TSN bridge are promising to provide the required communication service.To guarantee the endto-end(E2E)QoS(Quality of Service)performance of traffic is a great challenge in 5G-TSN integrated networks.A dynamic QoS mapping method is proposed in this paper.It is based on the improved K-means clustering algorithm and the rough set theory(IKCRQM).The IKC-RQM designs a dynamic and loadaware QoS mapping algorithm to improve its flexibility.An adaptive semi-persistent scheduling(ASPS)mechanism is proposed to solve the challenging deterministic scheduling in 5GS.It includes two parts:one part is the persistent resource allocation for timesensitive flows,and the other part is the dynamic resource allocation based on the max-min fair share algorithm.Simulation results show that the proposed IKC-RQM algorithm achieves flexible and appropriate QoS mapping,and the ASPS performs corresponding resource allocations to guarantee the deterministic transmissions of time-sensitive flows in 5G-TSN integrated networks.展开更多
基金supported by National Key Research and Development Project under Grant No.2020YFB1710900Sichuan International Cooperation Project of Science and Technology Innovation under Grant No.2022YFH0022。
文摘The ubiquitous and deterministic communication systems are becoming indispensable for future vertical applications such as industrial automation systems and smart grids.5G-TSN(Time-Sensitive Networking)integrated networks with the 5G system(5GS)as a TSN bridge are promising to provide the required communication service.To guarantee the endto-end(E2E)QoS(Quality of Service)performance of traffic is a great challenge in 5G-TSN integrated networks.A dynamic QoS mapping method is proposed in this paper.It is based on the improved K-means clustering algorithm and the rough set theory(IKCRQM).The IKC-RQM designs a dynamic and loadaware QoS mapping algorithm to improve its flexibility.An adaptive semi-persistent scheduling(ASPS)mechanism is proposed to solve the challenging deterministic scheduling in 5GS.It includes two parts:one part is the persistent resource allocation for timesensitive flows,and the other part is the dynamic resource allocation based on the max-min fair share algorithm.Simulation results show that the proposed IKC-RQM algorithm achieves flexible and appropriate QoS mapping,and the ASPS performs corresponding resource allocations to guarantee the deterministic transmissions of time-sensitive flows in 5G-TSN integrated networks.
文摘为了解决智能制造领域中云化控制与视觉分选应用相结合的问题,提出了基于深度学习的云化可编程逻辑控制器(Programmable logic controller,PLC)物料识别与定位系统,并在端到端5G与时间敏感网络(Time sensitive networking,TSN)传输网络环境下,实现了对云化PLC架构和控制功能有效性的验证.首先,将传统PLC系统控制功能容器虚拟化,实现PLC的本地和云端自由部署;其次,在云端设计人工智能学习平台,采用基于You only look once v5(YOLOv5)的目标检测算法实现物料的定位和分类,获取目标的像素坐标和类别信息;然后,利用相机标定方法把像素坐标转换成物理世界坐标,并将目标类别、坐标、时间戳信息传输到云化PLC;最后,在5G和TSN融合网络环境下,实现云化PLC对天车设备的实时控制与复杂计算功能整合.结果表明,该系统能够有效的对多天车进行协同控制,物料定位均值平均精度(Mean average precision,mAP)达到99.65%,分选准确率达到96.67%,平均消耗时间225.99 s,满足工业低时延、高精度的视觉分选需求.
