Concordia: Enabling Low-Conflict Distributed Transaction Scheduling in Sharding Blockchain via Cooperative Perception

Sharding is a key approach to scale blockchain, where transaction scheduling critically impacts performance. Traditional sharding uses non-perception scheduling, where each shard makes decisions independently, leading to high conflicts. Although some studies use a centralized scheduler to eliminate conflicts by gathering full shard data, but incur security risks. To address this, we propose Concordia, a distributed transaction scheduling scheme via cooperative perception. Each shard predicts future cross-shard interactions via a Graph Neural Network (GNN) based algorithm, generates low-dimensional perception signals, and shares them through incremental personalized broadcasts. Shards then use a popularity-driven transaction packing algorithm to schedule and pack transactions effectively. With 16 shards, Concordia achieves 2.39x higher throughput than non-perception scheduling while cutting conflicts from 62.3% to 1.5%, and improves throughput 1.67x over centralized scheduling while reducing perception overhead by 95.2%.