Abstract
In geo-distributed deployments, sensor data are collected under the coordination of smart terminals and relayed on-chain via decentralized oracles. A motivating scenario involves healthcare networks where regional hospitals submit aggregated medical data to blockchain systems while maintaining strict information security-often designating one gateway per region for external communication. Long geographical distances between smart terminals stress traditional consensus with excessive network overhead and limited efficiency. To address this, we propose a layered BFT consensus method, 2-layer EaZy BFT (2EZBFT). The system forms multiple independent groups of smart terminals and builds a two-layer consensus architecture-"intra-group synchronization, inter-group consensus"-to complete cross-group data aggregation and final on-chain consensus. This layered design reduces intra-group communication complexity by lowering the number of nodes per group and reduces cross-group interactions via leader-side aggregation, thereby lowering overall network overhead. Compared with other BFT algorithms, the proposed scheme improves the efficiency of data collection and on-chain reporting while ensuring consensus security and consistency. Experiments show improvements in metrics such as network overhead and consensus latency. In a discrete-event simulation with an asymmetric WAN latency matrix and geo-partitioned groups, 2EZBFT achieves up to 45% higher throughput than flat BFT algorithms such as PBFT and HotStuff under high load. It provides a practical path for efficient data interaction in decentralized oracles and offers guidance for improving the performance of blockchain-real-world data exchange.