Real-Time Communication Model Based on OPC UA Wireless Network for Intelligent Production Line

被引:4
作者
Chai, Anying [1 ,2 ,3 ]
Ma, Yue [2 ,3 ]
Yin, Zhenyu [2 ,3 ]
Li, Mingshi [1 ,2 ,3 ]
机构
[1] Univ Chinese Acad Sci, Fac Comp Sci & Technol, Beijing 100049, Peoples R China
[2] Chinese Acad Sci, Shenyang Inst Comp Technol, Shenyang 110168, Peoples R China
[3] Liaoning Key Lab Domest Ind Control Platform Tech, Shenyang 110168, Peoples R China
关键词
Production; Real-time systems; Wireless networks; Wireless sensor networks; Job shop scheduling; Dynamic scheduling; Reliability; Industrial wireless network; OPC Unified Architecture; real-time; service differentiation; preemptive; ARCHITECTURE; IMPLEMENTATION; SCHEME;
D O I
10.1109/ACCESS.2021.3097399
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
With the continuous development of intelligent manufacturing technology, the intelligent production line for the Industrial Internet of Things occupies an important position in the field of industrial intelligence. OPC UA is a standard for communication data exchange between intelligent production line devices. OPC UA can establish a unified information model for production line devices and improve the connectivity of heterogeneous networks. However, in industrial wireless network application scenarios, there are various types of sensing information and large amounts of data to be transmitted. Each type of data has different requirements for real-time. The traditional OPC UA communication method is difficult to achieve real-time and reliable transmission in intelligent production lines and can't meet the transmission requirements of time-sensitive data. In this paper, we propose a real-time communication model of the OPC UA wireless network for intelligent production lines (UAMPDS). IEEE 802.15.4e TSCH is used as the wireless communication infrastructure, and OPC UA protocols are fused to this model. Meanwhile, we design a load-aware time-slot scheduling algorithm to dynamically allocate and schedule time slots according to the network topology and traffic load of each node. We also implement a dynamic preemptive resource scheduling strategy based on service differentiation to ensure real-time transmission of time-sensitive data. The experimental results show that this model achieves differentiated services based on data with different latency tolerance and effectively reduces the transmission latency of real-time service data under the constrained network resources. It can avoid the starvation phenomenon of low priority queues, and improves the overall quality of service of intelligent production line communication networks.
引用
收藏
页码:102312 / 102326
页数:15
相关论文
共 38 条
[1]   QoS-Aware IIoT Microservices Architecture [J].
Al-Masri, Eyhab .
2018 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL INTERNET (ICII 2018), 2018, :171-172
[2]   Limited Preemptive Scheduling for Real-Time Systems. A Survey [J].
Buttazzo, Giorgio C. ;
Bertogna, Marko ;
Yao, Gang .
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2013, 9 (01) :3-15
[3]   Design and Implementation of a Service-Oriented Architecture for the Optimization of Industrial Applications [J].
Girbea, Alina ;
Suciu, Constantin ;
Nechifor, Septimiu ;
Sisak, Francisc .
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2014, 10 (01) :185-196
[4]  
Han L., 2017, INF TECHNOL STANDARD, V2017, P30
[5]   NFV and Blockchain Enabled 5G for Ultra-Reliable and Low-Latency Communications in Industry: Architecture and Performance Evaluation [J].
Huang, Haojun ;
Miao, Wang ;
Min, Geyong ;
Tian, Jialin ;
Alamri, Atif .
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2021, 17 (08) :5595-5604
[6]   A Novel CPPS Architecture Integrated with Centralized OPC UA server for 5G-based Smart Manufacturing [J].
Kim, Jeehyeong ;
Jo, Guejong ;
Jeong, Jongpil .
16TH INTERNATIONAL CONFERENCE ON MOBILE SYSTEMS AND PERVASIVE COMPUTING (MOBISPC 2019),THE 14TH INTERNATIONAL CONFERENCE ON FUTURE NETWORKS AND COMMUNICATIONS (FNC-2019),THE 9TH INTERNATIONAL CONFERENCE ON SUSTAINABLE ENERGY INFORMATION TECHNOLOGY, 2019, 155 :113-120
[7]   National cyber security enhancement scheme for intelligent surveillance capacity with public IoT environment [J].
Kim, Kwangho ;
Kim, InJung ;
Lim, Jongin .
JOURNAL OF SUPERCOMPUTING, 2017, 73 (03) :1140-1151
[8]   Standalone OPC UA Wrapper for Industrial Monitoring and Control Systems [J].
Kim, Woonggy ;
Sung, Minyoung .
IEEE ACCESS, 2018, 6 :36557-36570
[9]   A review of industrial wireless networks in the context of Industry 4.0 [J].
Li, Xiaomin ;
Li, Di ;
Wan, Jiafu ;
Vasilakos, Athanasios V. ;
Lai, Chin-Feng ;
Wang, Shiyong .
WIRELESS NETWORKS, 2017, 23 (01) :23-41
[10]  
[刘纯尧 Liu Chunyao], 2015, [计算机科学, Computer Science], V42, P28