Cardano recently upgraded its sanitation method with the latest solution for scaling consensus layers, pipelining. It will be an important part of Cardano’s scaling plan in 2022 to support the ever-expanding Cardano ecosystem. As Cardano enters Basho’s development phase, the network is focused on meeting growing market needs. So the Cardano team is working on its Ouroboros Praos and maintaining the speed of dApps that are drafted or deployed on Cardano. Cardano has a lot to offer and the price reflects that. Many people familiar with the world of digital currencies and tokens believe that ADA-USD is the future of the industry. According to Cardano projections, ADA will eventually compete with and eventually replace larger cryptos such as ETH and BTC. The network will be steadily optimized in a series of measured steps, scaling Cardano methodically and carefully for upcoming growth as demand increases. The changes released in the network’s 1.33.0 node gave Cardano more room to improve on some network parameters. Network parameters such as memory units and block size can be changed. The changes directly affect how Cardano maintains network traffic and monitors network performance. In addition, Cardano’s close observation of the real-world performance of Ouroboros Praos and the accumulated impact of parameters will play a critical role throughout the procedure. After each update, the network carefully evaluates and monitors at least one epoch before moving forward with additional adjustments. Diffusion pipelining will act as the evolution for the consensus layer allowing for faster block propagation. It will enable even greater gains in headroom, enabling additional upgrades in network competitiveness and performance. The integration will improve the block addition protocol, which currently runs as follows: Block transmission Blick validation Block body transmission and request Block header transmission Block body transmission Although this systematic sequence has been working for several years, the increasing number of blocks hinders the system. Therefore, the diffusion pipeline will perform the steps afterward, saving time and increasing the output.