Publication Type : Conference Paper
Publisher : IEEE
Source : 2025 3rd International Conference on Intelligent Data Communication Technologies and Internet of Things (IDCIoT)
Url : https://doi.org/10.1109/idciot64235.2025.10915108
Campus : Bengaluru
School : School of Computing
Department : Computer Science and Engineering
Year : 2025
Abstract : Time-Sensitive Networking (TSN) has recently become an important standard to support time-sensitive reliable low-latency data transmission in industrial and real-time applications. This work explores the use of different traffic shaping algorithms, namely, credit-based shaping (CBS) and time-aware shaping (TAS) alongside frame preemption-a TSN instance which gives precedence to high-importance frames by means of lower-priority traffic interruption-to extend TSN's traffic management capabilities. By controlling data flow and allowing for high priority packets to pass through unimpeded, traffic shaping algorithms serve an essential function in making the network more efficient and reducing congestion rates. The work compares these algorithms in isolation and also in combination over a network model, comprising of four switches and three end users for each switch, using the OMNeT++ simulation environment. This study aims to contribute insights into optimal shaping techniques for TSN, enhancing its suitability for critical network applications.
Cite this Research Publication : Archana Reddy Penumada, Divya Jyothi Gundapaneni, Akshitha Chennupati, Shinu M Rajagopal, Integration of Traffic Shaping with Time-Sensitive Networking for Effective Traffic Management, 2025 3rd International Conference on Intelligent Data Communication Technologies and Internet of Things (IDCIoT), IEEE, 2025, https://doi.org/10.1109/idciot64235.2025.10915108