Public research artifact for reproducible blockchain benchmarking under controlled network topologies, realistic workloads, and repeatable experimental conditions.

Artifact overview

Lilith connects blockchain workload execution, programmable network emulation, deployment orchestration, monitoring, and analysis scripts into a research-oriented benchmarking workflow. It was designed to evaluate blockchain systems under controlled network topologies that expose latency, bandwidth, workload, and implementation effects.

What Lilith does

• Runs blockchain benchmarking experiments under configurable topology-aware network conditions.
• Integrates workload generation, network emulation, orchestration scripts, configuration, and analysis utilities.
• Supports reproducible evaluation workflows for comparing performance, latency, energy usage, and run-to-run variability.
• Provides a practical bridge between research questions and executable experimental artifacts.

Why topology-aware benchmarking matters

Blockchain systems are distributed by design, so their behaviour depends on more than protocol logic or raw machine speed. Network structure, latency, bandwidth, workload shape, validator placement, and deployment assumptions can all affect throughput, latency, energy consumption, and experimental repeatability. Lilith makes these factors explicit and controllable.

Repository highlights

• Public repository layout for a research artifact around topology-aware blockchain benchmarking.
• Example machine template for local configuration.
• Local validation mode for checking the repository and experiment configuration before heavier runs.
• Git LFS tracking for the large cloud-ping dataset used by the topology and latency workflow.
• Documentation for execution modes, repository layout, quick validation, and reproducibility-oriented usage.

Main research use cases

• Evaluate blockchain performance across different network topologies and workloads.
• Study topology effects on throughput, latency, energy consumption, and commit behaviour.
• Compare blockchain implementations under controlled and repeatable experimental assumptions.
• Support artifact-based reproducibility for peer-reviewed blockchain systems research.

Connection to my PhD work

Lilith was developed as part of my doctoral research on comparing blockchains through performance, energy, repeatability, predictability, and economic-efficiency perspectives. The framework supports the topology-aware benchmarking line of work behind my ACM DLT journal article, DEBS '25, and ICBC '25 research outputs.