A Fast Consensus Algorithm of Large-Scale Heterogeneous Dynamic IoT Nodes for DAG-Based Blockchain

To solve issues of frequent network topology changes to slow consensus speed, and low security in consensus algorithms within heterogeneous dynamic IoT systems, we propose a fast consensus algorithm of large-scale heterogeneous dynamic IoT nodes for DAG-based blockchain, LSHD_DAG. Firstly, an adaptive regional division method for heterogeneous dynamic nodes is proposed, which monitors nodes’ state and counts within each region, adjusting the boundaries of adjacent regions. Secondly, an event-triggered master-slave DAG chain design is proposed. When transaction information pertains to a single region, the transaction is processed as a local transaction to construct a regional DAG slave chain. If transaction information involves multiple regions, it is organized into a multi-regional transaction set and incorporated into the global DAG master chain. Next, a node grade identification mechanism that balances state and reputation factors is proposed. This mechanism adopts the LOF algorithm to classify or dynamically update node grades by considering node state and reputation evaluation results, assigning them identity permissions. Finally, a weighted voting consensus based on the master-slave DAG chain is introduced. Nearby honest nodes with stable movement are selected as consensus nodes, which perform multi-regional weighted voting consensus on transactions and transaction sets. This process concludes with Two-Way Pegging with multi-signature on the master-slave DAG, ensuring secure and rapid consensus for data in heterogeneous and dynamic IoT environments. The experimental results show that no matter how the number of nodes changes, LSHD_DAG can improve transaction throughput, and reduce latency and communication overhead, outperforming the CDBFT, DAG-D, and Avalanche.