Improved End to End Delay in CBS Using Data Compression for Time Sensitive Network

Abstract

TSN or Time-Sensitive Network is an accumulation of standards that can provide the Ethernet network with an extension to support the real-time application while maintaining the safety-critical distribution with the hardware. To enhance real-time guarantees, TSN adopts several shaping Credit-Based Shaping, Asynchronous Traffic Shaping (ATS), Burst-Limiting Shaper (BLS), and scheduling mechanisms such as Time Aware Shaper (TAS) and numerous types of traffic are integrated. In modern industries, the increasing number of traffic and data is causing 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 it is applicable for the worst-case scenarios as well. Moreover, the focus of this research is confined to the CBS shaping mechanism. For the validation of our statement, various traffic such as Control Data Traffic (CDT), Audio & Video Bridging (AVB) class A, AVB class B, and best-effort have been simulated using OMNeT++. Comparisons are shown in terms of end-to-end delay between the compressed and the uncompressed data, and end-to-end delay has been improved for all classes.