Towards Developing a Supervisory Agent for Adapting the QoS Network ConfigurationsShow others and affiliations
2024 (English)In: IEEE International Conference on Emerging Technologies and Factory Automation, ETFA, Institute of Electrical and Electronics Engineers (IEEE) , 2024Conference paper, Published paper (Refereed)
Abstract [en]
As the industry trend is moving toward Ethernet-based Industrial Control Systems (ICSs) in line with the industry 4.0 paradigm, the network traffic must be monitored and managed to keep the systems reliably available. A flat converged network architecture where all the controllers, Input/Output (I/O), and supervisory systems are connected introduces mixed traffic classes competing for network resources and access to the shared medium. These traffic classes are typically managed with different Quality of Service (QoS) techniques. The challenge lies in managing end-to-end QoS in a heterogeneous environment and configuring switches according to the vendor, model, and operating software. Meanwhile, emerging greenfield technology are not deployable with switches used in today's ICS. We propose a distributed QoS supervisory agent, capable of detecting and correcting faulty QoS configurations in a contemporary heterogeneous Layer 2 switch environment. The initial results are achieved through two experimental testbeds in a use case where our agent successfully corrected the QoS configurations. © 2024 IEEE.
Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2024.
Keywords [en]
Faulty QoS Detection and Correction, Industrial Control Systems, QoS Supervision, Autonomous agents, Carrier sense multiple access, Critical path analysis, Microelectronics, Faulty quality of service detection and correction, Industry trends, Network configuration, Quality of service supervision, Quality-of-service, Service configuration, Services network, Traffic class, Quality of service
National Category
Telecommunications
Identifiers
URN: urn:nbn:se:mdh:diva-69008DOI: 10.1109/ETFA61755.2024.10710969ISI: 001535140200197Scopus ID: 2-s2.0-85207824142ISBN: 9798350361230 (print)OAI: oai:DiVA.org:mdh-69008DiVA, id: diva2:1912937
Conference
29th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2024, Padova 10 September 2024 through 13 September 2024
2024-11-132024-11-132025-10-10Bibliographically approved