A Generic Framework for Optimization in Blockchain Simulators

TL;DR

This paper presents GFOBS, a flexible framework that standardizes and optimizes blockchain simulations, introducing innovative optimization techniques to improve efficiency and reproducibility in blockchain research.

Contribution

The paper introduces GFOBS, a versatile framework for blockchain simulation optimization, featuring a warm starting technique and a concurrent multiprocessing method.

Findings

Enhanced simulation efficiency through new optimization methods

Improved reproducibility and standardization of blockchain experiments

Demonstrated versatility across various blockchain research scenarios

Abstract

As blockchain technology rapidly evolves, researchers face a significant challenge due to diverse and non-standardized simulation parameters, which hinder the replicability and comparability of research methodologies. This paper introduces a Generic Framework for Optimization in Blockchain Simulators (GFOBS), a comprehensive and adaptable solution designed to standardize and optimize blockchain simulations. GFOBS provides a flexible platform that supports various optimization algorithms, variables, and objectives, thereby catering to a wide range of blockchain research needs. The paper's key contributions are threefold: the development of GFOBS as a versatile tool for blockchain simulation optimization; the introduction of an innovative optimization method using warm starting technique; and the proposition of a novel concurrent multiprocessing technique for simultaneous simulation processes. These advancements collectively enhance the efficiency, replicability, and standardization of blockchain simulation experiments.