BlockSim: An Extensible Simulation Tool for Blockchain Systems
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Abstract (arXiv)
Both in the design and deployment of blockchain solutions many performance-impacting configuration choices need to be made. We introduce BlockSim, a framework and software tool to build and simulate discrete-event dynamic systems models for blockchain systems. BlockSim is designed to support the analysis of a large variety of blockchains and blockchain deployments as well as a wide set of analysis questions. At the core of BlockSim is a Base Model, which contains the main model constructs common across various blockchain systems organized in three abstraction layers (network, consensus and incentives layer). The Base Model is usable for a wide variety of blockchain systems and can be extended easily to include system or deployment particulars. The BlockSim software tool provides a simulator that implements the Base Model in Python. This paper describes the Base Model, the simulator implementation, and the application of BlockSim to Bitcoin, Ethereum and other consensus algorithms. We validate BlockSim simulation results by comparison with performance results from actual systems and from other studies in the literature. We close the paper by a BlockSim simulation study of the impact of uncle blocks rewards on mining decentralization, for a variety of blockchain configurations.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). First posted on arXiv 28 Apr 2020.
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Citing papers per year: 2022: 1; 2023: 1; 2024: 0; 2025: 0; 2026: 1.
3 papers.
- 2022The Cost of Training Machine Learning Models over Distributed Data Sourcescited by 18
- 2023A Model-Based Machine Learning Approach for Assessing the Performance of Blockchain Applicationscited by 0
- 2026Spec2Twin-Chain: Orchestrating Bi-Level Optimization with LLMs for Blockchain Digital Twin Constructioncited by 0
- 2026Spec2Twin-Chain: Orchestrating Bi-Level Optimization with LLMs for Blockchain Digital Twin Construction30 Aug 2026
- 2023A Model-Based Machine Learning Approach for Assessing the Performance of Blockchain Applications20 Sep 2023
- 2022The Cost of Training Machine Learning Models over Distributed Data Sources15 Sep 2022