mycoreobjectrosdok_document_0000026269rosdok_document_0000026269rosdokdocumentrosdok_derivate_00002258462026-01-03T15:46:28.755Z2025-04-30T08:46:37.700ZMCRJANITOReditorKLpublished1rosdok_derivate_0000225846truetruederivate_types:fulltextVolltextfulltextwf_edit_epub wf_register_epubstate:publishedstate:publishedveröffentlichtpublishedrosdok/id00004769194773153XOau2026-01-032026-01-03T14:15:04ZrdaConverted from PICA to MODS using Pica2MODS XSLT Transformer 2.10 [SCM: "f6c168af690edb7cb65ef34e4a2bf7f8714c5d38" "v2.10" "2024-03-28T14:43:08+0100"] with mode 'DEFAULT'.Forschungsbericht/StudieTechnical Report on the Analysis and Simulation of Converged Data Traffic in Time-Sensitive NetworksTime-Sensitive Networking (TSN) is a key technology for converged industrial communication systems enabling the integration of traffic with diverse Quality of Service (QoS) requirements such as timeliness, throughput, and reliability. To ensure that all data streams meet their requirements, the Network Calculus (NC) allows to analytically derive worstcase performance estimations. In this paper, we model rate-constrained streams alongside time-triggered hard real-time traffic in a line topology. Additionally, we compare the analytical results with simulations conducted in the OMNeT++ network simulator. Our comparison shows that the worst-case delay predicted by the NC is 3 to 4 times higher than the delay observed in simulations. Similarly, the estimated backlog (i.e., the amount of data queued in TSN switches) is 1.25 to 2.8 times larger than the simulation results. A further experiment indicates that NC predictions are more accurate for less complex network configurations.JulianOertelVerfasserInaut0009-0000-5919-8638HelgeParzyjegla1980 -VerfasserInaut10461847760009-0005-1357-1341PeterDanielis1982 -VerfasserInaut10270859030000-0002-1976-9560https://purl.uni-rostock.de/rosdok/id00004769urn:nbn:de:gbv:28-rosdok_id00004769-610.18453/rosdok_id00004769004 InformatikFakultät für Informatik und ElektrotechnikCC BY-SA 4.0Nutzungsrechte erteiltLizenz Metadaten: CC0frei zugänglich (Open Access)en1 Online-Ressource (15 Seiten)2025December 16, 2025University of Rostock, Institute of Computer ScienceRostockmonographic2025Universitätsbibliothek RostockRostock2025Universitätsbibliothek Rostockhttps://purl.uni-rostock.de/rosdok/id00004769[{"name":"Oertel, Julian","orcid":"0009-0000-5919-8638"},{"name":"Parzyjegla, Helge","orcid":"0009-0005-1357-1341"},{"name":"Danielis, Peter","orcid":"0000-0002-1976-9560"}]Julian Oertel, Helge Parzyjegla, and Peter DanielisOertel, Julian0009-0000-5919-8638Parzyjegla, Helge0009-0005-1357-1341Danielis, Peter0000-0002-1976-9560doctype:epubdoctype:epubDokumenttypDocument typedoctype:epub.reportdoctype:epub.reportForschungsbericht/Studiereport/studydiniPublType:report diniPublType2022:Reportinfo:eu-repo/semantics/reportdocumentdiniPublType2022:ReportdiniPublType2022:ReportVerschiedenartige TexteReportDRIVERSDNB:004SDNB:004004 Informatik004 Data processing Computer sciencesinstitution:unirostockinstitution:unirostockUniversität RostockUniversity of RostockUniversität RostockUniversität RostockUni.Rostockhttp://d-nb.info/gnd/38329-6institution:unirostock.iefinstitution:unirostock.iefFakultät für Informatik und ElektrotechnikFaculty of Computer Science and Electrical EngineeringUniversität Rostock. Fakultät für Informatik und ElektrotechnikFakultät für Informatik<br />und ElektrotechnikUni.Rostock.Fakultaet.IEFhttp://d-nb.info/gnd/10085032-7licenseinfo:worklicenseinfo:workWerkworklicenseinfo:work.cclicenselicenseinfo:work.cclicenseCC-LizenzCC-licenselicenseinfo:work.cclicense.cc-by-salicenseinfo:work.cclicense.cc-by-saCC BY-SACC BY-SAlicenseinfo:work.cclicense.cc-by-sa.v40licenseinfo:work.cclicense.cc-by-sa.v40CC BY-SA 4.0CC BY-SA 4.0/creativecommons/l/by-sa/4.0/88x31.png[DE-28]Namensnennung - Weitergabe unter gleichen Bedingungen 4.0 International$cCC BY-SA 4.0$gCreative Commons$uhttps://creativecommons.org/licenses/by-sa/4.0/https://creativecommons.org/licenses/by-sa/4.0/https://creativecommons.org/licenses/by-sa/4.0/licenseinfo:depositlicenseinfo:depositVeröffentlichungsgenehmigungpermission to storelicenseinfo:deposit.rightsgrantedlicenseinfo:deposit.rightsgrantedNutzungsrechte erteiltrights grantedlicenseinfo:metadatalicenseinfo:metadataLizenzen für Metadatenlicenseinfo:metadata.cc0licenseinfo:metadata.cc0Lizenz Metadaten: CC0license metadata: CC0/creativecommons/p/zero/1.0/88x31.pnghttps://creativecommons.org/publicdomain/zero/1.0/accesscondition:openaccessaccesscondition:openaccessfrei zugänglich (Open Access)open accesshttp://purl.org/coar/access_right/c_abf2OAfreeinfo:eu-repo/semantics/openAccess[DE-28]Open Access$gControlled Vocabulary for Access Rights$uhttp://purl.org/coar/access_right/c_abf2rfc5646:enrfc5646:enEnglischEnglishengengTechnical Report on the Analysis and Simulation of Converged Data Traffic in Time-Sensitive NetworksTechnical Report on the Analysis and Simulation of Converged Data Traffic in Time-Sensitive Networksorcid:0009-0000-5919-8638gnd:1046184776orcid:0009-0005-1357-1341gnd:1027085903orcid:0000-0002-1976-9560orcid:0009-0000-5919-8638gnd:1046184776orcid:0009-0005-1357-1341gnd:1027085903orcid:0000-0002-1976-9560rosdok_document_0000026269-d1328118e49orcid:0009-0000-5919-8638Julian OertelJulian Oertelrosdok_document_0000026269-d1328118e61gnd:1046184776orcid:0009-0005-1357-1341Helge ParzyjeglaHelge Parzyjeglarosdok_document_0000026269-d1328118e77gnd:1027085903orcid:0000-0002-1976-9560Peter DanielisPeter DanielisJulian OertelHelge ParzyjeglaPeter DanielisJulian OertelHelge ParzyjeglaPeter DanielisJulian OertelHelge ParzyjeglaPeter DanielisRostockUniversity of Rostock, Institute of Computer Scienceepub.reporthttps://purl.uni-rostock.de/rosdok/id00004769urn:nbn:de:gbv:28-rosdok_id00004769-610.18453/rosdok_id00004769Time-Sensitive Networking (TSN) is a key technology for converged industrial communication systems enabling the integration of traffic with diverse Quality of Service (QoS) requirements such as timeliness, throughput, and reliability. To ensure that all data streams meet their requirements, the Network Calculus (NC) allows to analytically derive worstcase performance estimations. In this paper, we model rate-constrained streams alongside time-triggered hard real-time traffic in a line topology. Additionally, we compare the analytical results with simulations conducted in the OMNeT++ network simulator. Our comparison shows that the worst-case delay predicted by the NC is 3 to 4 times higher than the delay observed in simulations. Similarly, the estimated backlog (i.e., the amount of data queued in TSN switches) is 1.25 to 2.8 times larger than the simulation results. A further experiment indicates that NC predictions are more accurate for less complex network configurations.20252025[{"name":"Oertel, Julian","orcid":"0009-0000-5919-8638"},{"name":"Parzyjegla, Helge","orcid":"0009-0005-1357-1341"},{"name":"Danielis, Peter","orcid":"0000-0002-1976-9560"}]Julian Oertel, Helge Parzyjegla, and Peter Danielisepub.report1 Oertel_Analysis_2026.pdf 3187343 3983c4dc3cfec5f949adce78aa1afdf2 rosdok/id00004769194773153XOau2026-01-032026-01-03T14:15:04ZrdaConverted from PICA to MODS using Pica2MODS XSLT Transformer 2.10 [SCM: "f6c168af690edb7cb65ef34e4a2bf7f8714c5d38" "v2.10" "2024-03-28T14:43:08+0100"] with mode 'DEFAULT'.Forschungsbericht/StudieTechnical Report on the Analysis and Simulation of Converged Data Traffic in Time-Sensitive NetworksTime-Sensitive Networking (TSN) is a key technology for converged industrial communication systems enabling the integration of traffic with diverse Quality of Service (QoS) requirements such as timeliness, throughput, and reliability. To ensure that all data streams meet their requirements, the Network Calculus (NC) allows to analytically derive worstcase performance estimations. In this paper, we model rate-constrained streams alongside time-triggered hard real-time traffic in a line topology. Additionally, we compare the analytical results with simulations conducted in the OMNeT++ network simulator. Our comparison shows that the worst-case delay predicted by the NC is 3 to 4 times higher than the delay observed in simulations. Similarly, the estimated backlog (i.e., the amount of data queued in TSN switches) is 1.25 to 2.8 times larger than the simulation results. A further experiment indicates that NC predictions are more accurate for less complex network configurations.JulianOertelVerfasserInaut0009-0000-5919-8638HelgeParzyjegla1980 -VerfasserInaut10461847760009-0005-1357-1341PeterDanielis1982 -VerfasserInaut10270859030000-0002-1976-9560https://purl.uni-rostock.de/rosdok/id00004769urn:nbn:de:gbv:28-rosdok_id00004769-610.18453/rosdok_id00004769004 InformatikFakultät für Informatik und ElektrotechnikCC BY-SA 4.0Nutzungsrechte erteiltLizenz Metadaten: CC0frei zugänglich (Open Access)en1 Online-Ressource (15 Seiten)2025December 16, 2025University of Rostock, Institute of Computer ScienceRostockmonographic2025Universitätsbibliothek RostockRostock2025Universitätsbibliothek Rostockhttps://purl.uni-rostock.de/rosdok/id00004769[{"name":"Oertel, Julian","orcid":"0009-0000-5919-8638"},{"name":"Parzyjegla, Helge","orcid":"0009-0005-1357-1341"},{"name":"Danielis, Peter","orcid":"0000-0002-1976-9560"}]Julian Oertel, Helge Parzyjegla, and Peter Danielis Oertel, Julian 0009-0000-5919-8638 Parzyjegla, Helge 0009-0005-1357-1341 Danielis, Peter 0000-0002-1976-9560 2025-04-30T08:46:37.700Z 2026-01-03T15:46:28.755Z 2026-01-13T15:46:28.765Z editorKL {"identifier":"rosdok/id00004769","type":"local_id","additional":"","service":"MCRLocalID","created":"2025-04-30T08:46:37.755Z"} {"identifier":"urn:nbn:de:gbv:28-rosdok_id00004769-6","type":"dnbUrn","additional":"","service":"RosDokURN","created":"2025-04-30T08:46:37.786Z"} {"identifier":"https://purl.uni-rostock.de/rosdok/id00004769","type":"purl","additional":"","service":"RosDokPURL","created":"2025-04-30T08:46:37.797Z","registrationStarted":"2026-01-03T15:46:27.348Z"} {"identifier":"10.18453/rosdok_id00004769","type":"doi","additional":"","service":"RosDokDOI","created":"2025-04-30T08:46:37.806Z","registrationStarted":"2026-01-03T14:08:39.358Z","registered":"2026-01-03T15:46:28.750Z"} MCRJANITORfulltextfile/rosdok_document_0000026269/rosdok_derivate_0000225846/Oertel_Analysis_2026.pdfTechnical Report on the Analysis and Simulation of Converged Data Traffic in Time-Sensitive NetworksTechnical Report on the Analysis and Simulation of Converged Data Traffic in Time-Sensitive Networksorcid:0009-0000-5919-8638gnd:1046184776orcid:0009-0005-1357-1341gnd:1027085903orcid:0000-0002-1976-9560orcid:0009-0000-5919-8638gnd:1046184776orcid:0009-0005-1357-1341gnd:1027085903orcid:0000-0002-1976-9560rosdok_document_0000026269-d1328118e49orcid:0009-0000-5919-8638Julian OertelJulian Oertelrosdok_document_0000026269-d1328118e61gnd:1046184776orcid:0009-0005-1357-1341Helge ParzyjeglaHelge Parzyjeglarosdok_document_0000026269-d1328118e77gnd:1027085903orcid:0000-0002-1976-9560Peter DanielisPeter DanielisJulian OertelHelge ParzyjeglaPeter DanielisJulian OertelHelge ParzyjeglaPeter DanielisJulian OertelHelge ParzyjeglaPeter DanielisRostockUniversity of Rostock, Institute of Computer Scienceepub.reporthttps://purl.uni-rostock.de/rosdok/id00004769urn:nbn:de:gbv:28-rosdok_id00004769-610.18453/rosdok_id00004769Time-Sensitive Networking (TSN) is a key technology for converged industrial communication systems enabling the integration of traffic with diverse Quality of Service (QoS) requirements such as timeliness, throughput, and reliability. To ensure that all data streams meet their requirements, the Network Calculus (NC) allows to analytically derive worstcase performance estimations. In this paper, we model rate-constrained streams alongside time-triggered hard real-time traffic in a line topology. Additionally, we compare the analytical results with simulations conducted in the OMNeT++ network simulator. Our comparison shows that the worst-case delay predicted by the NC is 3 to 4 times higher than the delay observed in simulations. Similarly, the estimated backlog (i.e., the amount of data queued in TSN switches) is 1.25 to 2.8 times larger than the simulation results. A further experiment indicates that NC predictions are more accurate for less complex network configurations.20252025[{"name":"Oertel, Julian","orcid":"0009-0000-5919-8638"},{"name":"Parzyjegla, Helge","orcid":"0009-0005-1357-1341"},{"name":"Danielis, Peter","orcid":"0000-0002-1976-9560"}]Julian Oertel, Helge Parzyjegla, and Peter Danielis[xslt]Saxonrosdok/id00004769https://purl.uni-rostock.de/rosdok/id00004769194773153X10.18453/rosdok_id00004769urn:nbn:de:gbv:28-rosdok_id00004769-6Julian Oertel, Helge Parzyjegla, Peter DanielisOertel Julian, Parzyjegla Helge, Danielis PeterTechnical Report on the Analysis and Simulation of Converged Data Traffic in Time-Sensitive NetworksForschungsbericht/Studiereport/studyUniversity of Rostock, Institute of Computer Science, December 16, 2025Time-Sensitive Networking (TSN) is a key technology for converged industrial communication systems enabling the integration of traffic with diverse Quality of Service (QoS) requirements such as timeliness, throughput, and reliability. To ensure that all data streams meet their requirements, the…Julian OertelHelge ParzyjeglaPeter DanielisTechnical Report on the Analysis and Simulation of Converged Data Traffic in Time-Sensitive NetworksUniversitätsbibliothek Rostockhttps://purl.uni-rostock.de/rosdok/id00004769JulianOertelVerfasserInaut0009-0000-5919-8638HelgeParzyjegla1980 -VerfasserInaut10461847760009-0005-1357-1341PeterDanielis1982 -VerfasserInaut10270859030000-0002-1976-9560[purl]https://purl.uni-rostock.de/rosdok/id00004769[urn]urn:nbn:de:gbv:28-rosdok_id00004769-6[doi]10.18453/rosdok_id00004769open_access20252025epoch:21th_centuryrfc5646:endoctype:epub.reportaccesscondition:openaccessSDNB:004institution:unirostock.iefstate:published