MANDALA: A scalable blockchain model with mesh-and-spoke network and H-PBFT consensus algorithm

With the rapid development of blockchain technology, the scale of its participants continues to expand. The network structure and the PBFT consensus algorithm of the blockchain have problems such as low transmission efficiency and high communication overhead, resulting in poor scalability. To solve these problems, we aim to improve the scalability of the blockchain so that it can support large-scale nodes for efficient transmission and communication. In this study, we propose a model named MANDALA with Mesh-and-Spoke Network and H-PBFT Consensus. The Mesh-and-Spoke network groups nodes into different layers and regulates communication rules among groups, which improves the network transmission efficiency. Then, we propose the Hierarchical Practical Byzantine Fault Tolerance (H-PBFT) consensus algorithm. It divides the consensus of the whole network into several sub-layers, which achieves lower communication complexity and improves fault tolerance. We simulated the model to validate its performance and security. The results indicated that it reduced the communication overhead and improved the effective transmission rate and throughput under the premise of ensuring security. Compared with other blockchain optimization schemes, our model features better consensus efficiency, security, and scalability.