Time-Sensitive Networking for industrial IoT: integration, analysis, and performance evaluation

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dc.check.chapterOfThesisNoneen
dc.contributor.advisorPesch, Dirk H J
dc.contributor.advisorZahran, Ahmed
dc.contributor.authorSeliem, Mohamed
dc.contributor.funderScience Foundation Irelanden
dc.date.accessioned2024-09-17T15:03:44Z
dc.date.available2024-09-17T15:03:44Z
dc.date.issued2024
dc.date.submitted2024
dc.description.abstractIndustrial automation networks demand precise timing, minimal latency, and negligible packet loss for efficient real-time data exchange. Time-Sensitive Networking (TSN) emerges as a crucial technology for future automation, promis ing enhanced timing accuracy, reduced packet delay, and improved networking determinism. This thesis explores and innovates within TSN functionalities to address key aspects of industrial networking and related technologies. The critical need for reliable real-time data exchange across industries is examined, introducing TSN principles such as time synchronisation, deterministic communication, traffic shaping, and Quality of Service (QoS) assurances. Through simulation, typical industrial use cases and traffic requirements are evaluated, focusing on priority queuing, Time Aware shaping (TAS), and Credit Based Shaping (CBS) to meet latency constraints. The findings demonstrate TSN’s ability to orchestrate network traffic while adhering to strict timing requirements, highlighting its practical relevance in industrial automation. In smart manufacturing environments, the optimisation of industrial networks for Quality Control and Classification After Production (QCAP) is emphasised. By leveraging TSN standards, diverse QoS requirements are addressed to enhance efficiency and reliability. Fault tolerance in Industrial Internet of Things (IIoT) applications is also investigated using network calculus principles to analyse worst-case latency, providing insights into network performance and stability. The research integrates TSN with Software Defined Networks (SDN) to manage network configurations, focusing on traffic scheduling in industrial applications. Network-device contracts are proposed for traffic schedule computation and distribution, demonstrating scalability through Mininet emulation. Additionally, Wi-Fi is explored as a complementary technology for IoT applications, evaluating its potential to reduce latency and enhance industrial automation. This thesis offers a comprehensive analysis of TSN performance across various scenarios and its integration with complementary technologies, providing valuable insights for advancing industrial automation and connectivity within the industry 4.0 paradigm.en
dc.description.statusNot peer revieweden
dc.description.versionAccepted Versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationSeliem, M. 2024. Time-Sensitive Networking for industrial IoT: integration, analysis, and performance evaluation. PhD Thesis, University College Cork.
dc.identifier.endpage173
dc.identifier.urihttps://hdl.handle.net/10468/16388
dc.language.isoenen
dc.publisherUniversity College Corken
dc.relation.projectinfo:eu-repo/grantAgreement/SFI/SFI Research Centres Programme::Phase 1/16/RC/3918/IE/Confirm Centre for Smart Manufacturing/en
dc.rights© 2024, Mohamed Seliem.
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectTime-Sensitive Networking
dc.subjectSoftware-defined networking
dc.subjectNetwork calculus
dc.subjectPerformance evaluation
dc.subjectReal-time communication
dc.titleTime-Sensitive Networking for industrial IoT: integration, analysis, and performance evaluation
dc.typeDoctoral thesisen
dc.type.qualificationlevelDoctoralen
dc.type.qualificationnamePhD - Doctor of Philosophyen
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