Simulation-Based Performance Evaluation of Sharded Blockchain Architectures

2026-06-12

AI Summary

This study addresses the fundamental scalability limitations of public blockchains—namely, verification overhead, propagation latency, and fork risk—when increasing throughput. The authors present a high-fidelity discrete-event simulator built on SimPy that, for the first time, systematically quantifies the nonlinear relationship between the number of shards and system performance, revealing diminishing returns due to cross-shard coordination overhead. The framework meticulously models consensus protocols, communication dynamics, and parallel execution mechanisms, and supports diverse network topologies. Experimental results demonstrate that with 256 shards, the system achieves throughput of 1.6 million transactions per second (TPS) in a local data center environment and 600,000 TPS under global wide-area network conditions, thereby validating both the substantial throughput gains and practical limits of sharded blockchain architectures.

Abstract

Public blockchains continue to struggle with scalability because improving throughput is not as simple as increasing block size or reducing block interval. Larger blocks increase validation and transmission cost, while shorter intervals raise the likelihood of propagation delays, forks, and stale blocks. These limits motivate sharding, where transaction processing is divided across multiple parallel shard groups. In this work, we present a configurable SimPy-based discrete-event simulator for evaluating sharded blockchain architectures under controlled workload and network assumptions. The simulator models mining, verification, inter-shard coordination, block dissemination, measured throughput, average block time, and communication overhead. Our simulator achieves 1.6M TPS at 256 shards under a local datacenter-like setup and 0.6M TPS in a global WAN setup, showing strong throughput gains from parallel execution. However, the gains are not unbounded: beyond a certain number of shards, coordination traffic, synchronization, and network overhead begin to dominate, leading to diminishing returns.

Problem

• scalability
• sharding
• blockchain
• throughput
• network overhead

Innovation

• sharded blockchain
• discrete-event simulation
• scalability
• throughput evaluation
• inter-shard coordination