Optimized Blockchain Sharding Model Based on Node Trust and Allocation

Abstract

Sharding technology is a promising solution for improving the scalability of blockchain systems. However, it faces the problem of allocating suitable trusted nodes into separate shards to satisfy security and efficiency requirements. Existing blockchain sharding methods fail to consider shard trust difference, communication latency difference, and node count difference among shards. This tends to increase the risk of a blockchain failure. This work proposes a novel blockchain sharding model for node allocation by considering shard trust difference. Its key idea is to allocate nodes of different trust levels to suitable shards to make shards have almost the same trust, such that shards reliability increases and blockchain failure probability decreases. To reduce the communication delay among shards, this work considers the communication latency difference and node count difference among shards. It proposes a sharding algorithm to iteratively adjust node allocations such that an optimal or near-optimal node allocation set is obtained. Simulation results show that the proposed method can effectively improve shard security and the performance of blockchain sharding compared with two state-of-the-art methods, i.e., Monoxide and Rapidchain, in terms of throughput, latency, and blockchain failure probability.