Improved and Comparative End to End Delay Analysis in CBS and TAS using Data Compression for Time Sensitive Network

TSN, or Time-Sensitive Network, is a set of standards that allows an Ethernet network to be extended to serve real-time applications while ensuring safety-critical hardware delivery. TSN uses a variety of shaping and scheduling techniques, like Credit-Based Shaping, Asynchronous Traffic Shaping (ATS), Burst-Limiting Shaper (BLS), and Time Aware Shaper (TAS), to improve real-time guarantees. In modern industries, the increasing number of traffic and data are causing the latency to increase significantly. To minimize the end-to-end delay, it is highly required to have lossless compress data. This paper proposes some pre-existing lossless compression algorithms (Huffman, LZW, RLE), which are well suited for the TSN network. It can improve the end-to-end delay despite increasing data and is applicable for the worst-case scenarios. So, the focus of this research is confined to CBS and CBS+TAS shaping mechanism. For the validation of our statement, we have simulated various traffics such as Control Data Traffic (CDT), Audio & Video Bridging (AVB) class A, AVB class B and best-effort by OMNeT++. Comparisons are shown in terms of end-to-end delay between the compressed and uncompressed data and end-to-end delay have been improved for all classes.