Distributed consensus algorithms are essential for maintaining data reliability and consistency across computer networks, ensuring that all nodes agree to a single state despite failures or malicious disruptions. Despite the critical role of Byzantine Fault Tolerant State Machine Replication (BFT SMR) protocols in securing such systems, existing protocols like Practical Byzantine Fault Tolerance (PBFT) and HotStuff still struggle with scalability, particularly in large applications where latency and throughput are crucial. A notable tradeoff is that, for example, PBFT is able to utilize network resources very well, but has significant communication complexity for reaching consensus, especially in scenarios where leaders are faulty. HotStuff manages to reduce the communication complexity by streamlining the leader-change mechanism, but by doing so is unable to fully utilise network resources in most cases.

This thesis introduces Para-HotStuff, a new BFT SMR protocol designed to improve the performance of streamlined leader-based consensus protocols by enabling parallel processing of blocks. Para-HotStuff builds on the core functionality of HotStuff, maintaining its linear communication complexity while incorporating parallel voting features from PBFT to optimize resource utilization and network bandwidth. The performance of Para-HotStuff was evaluated and compared to HotStuff under various conditions and protocol configurations, showing improved throughput and latency, particularly in scenarios with high transaction loads. Further research could explore implementing further mechanisms to improve \name{} as well as doing more comprehensive evaluations on how it behaves in real-world settings.