Auswahl der wissenschaftlichen Literatur zum Thema „Time-Aware Shaper (TAS)“
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Zeitschriftenartikel zum Thema "Time-Aware Shaper (TAS)"
Nasrallah, Ahmed, Akhilesh S. Thyagaturu, Ziyad Alharbi, Cuixiang Wang, Xing Shao, Martin Reisslein und Hesham Elbakoury. „Performance Comparison of IEEE 802.1 TSN Time Aware Shaper (TAS) and Asynchronous Traffic Shaper (ATS)“. IEEE Access 7 (2019): 44165–81. http://dx.doi.org/10.1109/access.2019.2908613.
Der volle Inhalt der QuelleLiu, Chang, Yue Hong, Jin Wang, Chang Liu Sr., Li Tian und Jiangpei Xu. „Hierarchical Cross Traffic Scheduling Based on Time-Aware Shapers for Mobile Time-Sensitive Fronthaul Network“. Wireless Communications and Mobile Computing 2024 (15.04.2024): 1–9. http://dx.doi.org/10.1155/2024/8882006.
Der volle Inhalt der QuelleHesham ElBakoury, Martin Reisslein, Akhilesh S. Thyagaturu, Venkatraman Balasubramanian und Ahmed Nasrallah. „Reconfiguration algorithms for high precision communications in time sensitive networks: Time-aware shaper configuration with IEEE 802.1Qcc“. ITU Journal on Future and Evolving Technologies 2, Nr. 1 (15.03.2021): 13–34. http://dx.doi.org/10.52953/sivv2522.
Der volle Inhalt der QuelleGuo, Mengjie, Guochu Shou, Yaqiong Liu und Yihong Hu. „Software-Defined Time-Sensitive Networking for Cross-Domain Deterministic Transmission“. Electronics 13, Nr. 7 (27.03.2024): 1246. http://dx.doi.org/10.3390/electronics13071246.
Der volle Inhalt der QuelleLuo, Feng, Bowen Wang, Zhenyu Yang, Ping Zhang, Yifei Ma, Zihao Fang, Mingzhi Wu und Zhipeng Sun. „Design Methodology of Automotive Time-Sensitive Network System Based on OMNeT++ Simulation System“. Sensors 22, Nr. 12 (17.06.2022): 4580. http://dx.doi.org/10.3390/s22124580.
Der volle Inhalt der QuelleAgustí-Torra, Anna, Marc Ferré-Mancebo, Gabriel David Orozco-Urrutia, David Rincón-Rivera und David Remondo. „A Microservices-Based Control Plane for Time-Sensitive Networking“. Future Internet 16, Nr. 4 (01.04.2024): 120. http://dx.doi.org/10.3390/fi16040120.
Der volle Inhalt der QuelleMunir, Haniya. „Language Shapes Socially Constructed Gender Roles: Ibsen’s ‘A Doll’s House’ in Focus“. Journal of Communication and Cultural Trends 2, Nr. 1 (05.01.2021): 19–30. http://dx.doi.org/10.32350/jcct/2020/21/1129.
Der volle Inhalt der QuelleMunir, Haniya. „Language Shapes Socially Constructed Gender Roles: Ibsen’s ‘A Doll’s House’ in Focus“. Journal of Communication and Cultural Trends 2, Nr. 1 (03.03.2021): 19–30. http://dx.doi.org/10.32350/jcct.21.02.
Der volle Inhalt der QuellePorras-Bernardez, Francisco, Georg Gartner, Nico Van de Weghe und Steven Verstockt. „Finding cultural heritage traces from modern social media“. Abstracts of the ICA 1 (15.07.2019): 1–2. http://dx.doi.org/10.5194/ica-abs-1-302-2019.
Der volle Inhalt der QuellePop, Paul, Konstantinos Alexandris und Tongtong Wang. „Configuration of multi‐shaper Time‐Sensitive Networking for industrial applications“. IET Networks, 30.06.2024. http://dx.doi.org/10.1049/ntw2.12129.
Der volle Inhalt der QuelleDissertationen zum Thema "Time-Aware Shaper (TAS)"
Roberty, Adrien. „Ordonnancer le trafic dans des réseaux déterministes grâce à l’apprentissage par renforcement“. Electronic Thesis or Diss., Chasseneuil-du-Poitou, Ecole nationale supérieure de mécanique et d'aérotechnique, 2024. http://www.theses.fr/2024ESMA0001.
Der volle Inhalt der QuelleOne of the most disruptive changes brought by Industry 4.0 is the networking of production facilities. Furthermore, the discussions on Industry 5.0 show the need for an integrated industrial ecosystem,combining AI and the digital twin. In this environment, industrial equipment will work seamlessly with human workers, requiring minimal latency, high-speed connectivity for real-time monitoring. In order to meet this requirement, the Time-Sensitive Networking (TSN) set of standards was introduced. However, configuring TSN in a complex industrial network poses new challenges. For example, the TSN standard allow some flexibility and modularity in the data plane, however, the mechanisms defined by these standards depends on many parameters (such as network topology, routing, etc.) which makes the design work difficult. IEEE 802.1Q is one of the main TSN standards that provides several mechanisms to achieve deterministic latency. One of them is called Time-Aware Shaper (TAS). A switch with a TAS function divides the data traffic, through multiple priorities, into multiple queues arranged in a regular schedule. The main way to organize this process is based on exact or heuristic methods. These are good for closed networks (when all streams are identified in advance and the network topology is fixed). However, in an open network (where more streams are added to the network and the network topology is dynamic), scheduling in TSN can lead to NP-hard problems. The goal of this thesis is to propose a solution to process the scheduling in TSN using Deep Reinforcement Learning with the use of simulations to train and evaluate the configuration agent
Buchteile zum Thema "Time-Aware Shaper (TAS)"
Johnson, Dale A. „Introduction“. In The Changing Shape Of English Nonconformity, 1825-1925, 3–12. Oxford University PressNew York, NY, 1998. http://dx.doi.org/10.1093/oso/9780195121636.003.0001.
Der volle Inhalt der QuelleKonferenzberichte zum Thema "Time-Aware Shaper (TAS)"
Li, Xiaotong, und Ao Jiang. „The impact of prevalent behavioural mimicry in adolescents on disease prevention and maintenance of healthy behavioural activation“. In 14th International Conference on Applied Human Factors and Ergonomics (AHFE 2023). AHFE International, 2023. http://dx.doi.org/10.54941/ahfe1003476.
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