Author(s)

Hong A’lan

Corresponding Author

Hong A’lan

Abstract

This paper proposes several performance optimization methods, including the improved DPoS algorithm based on node responsibility monitoring (Tower BFT-DPoSR), performance improvements for blockchain systems through hybrid distributed consensus and P2P optimization, the enhanced RAFT algorithm with parallel batch processing (PB-RAFT), and an efficient consensus algorithm involving regional representatives (ER-PBFT). These methods aim to increase transaction processing speed, reduce energy consumption, shorten confirmation time, and enhance the decentralization and security of blockchain systems. Through simulation experiments, this paper compares the performance of Tower BFT-DPoSR algorithm with traditional DPoS, Hybrid-P2P, PB-RAFT and ER-PBFT algorithms in throughput, confirmation time, energy consumption, decentralization degree, security and fault tolerance. The results show that the Tower BFT-DPoSR algorithm has the highest throughput and the lowest energy consumption under all network scales, and has significant advantages in confirmation time. In addition, the algorithm achieves a high degree of decentralization and good fault tolerance through its innovative responsibility evaluation system and hierarchical network model, making it an ideal choice for large-scale and highly concurrent blockchain network scenarios. The research in this paper provides scientific basis and practical guidance for improving the performance of blockchain technology, and lays a solid foundation for building a more efficient, safe and extensible blockchain ecosystem.

Keywords

blockchain; performance optimization; comparative study; distributed consensus algorithm; BFT-DPoSR; PB-RAFT; ER-PBFT; Hybrid-P2P