Evolutionary Random Graph for Bitcoin Overlay and Blockchain Mining Networks
Jacques Bou Abdo, Shuvalaxmi Dass, Basheer Qolomany, Liaquat Hossain

TL;DR
This paper introduces a new evolutionary random graph model to accurately represent and analyze the Bitcoin miner network, enabling better predictions of network stability, forking, and resilience during economic fluctuations.
Contribution
The paper presents a novel theoretical model for Bitcoin miner networks, validated with real data, improving understanding of network dynamics and resilience predictions.
Findings
Model accurately predicts network size and forking events.
Enables assessment of network resilience during price drops.
Provides insights into optimal mining difficulty settings.
Abstract
The world economy is experiencing the novel adoption of distributed currencies that are free from the control of central banks. Distributed currencies suffer from extreme volatility, and this can lead to catastrophic implications during future economic crisis. Understanding the dynamics of this new type of currencies is vital for empowering supervisory bodies from current reactive and manual incident responders to more proactive and well-informed planners. Bitcoin, the first and dominant distributed cryptocurrency, is still notoriously vague, especially for a financial instrument with market value exceeding 1 trillion. Modeling of bitcoin overlay network poses a number of important theoretical and methodological challenges. Current measuring approaches, for example, fail to identify the real network size of bitcoin miners. This drastically undermines the ability to predict forks, the…
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Taxonomy
TopicsBlockchain Technology Applications and Security · Complex Network Analysis Techniques · Peer-to-Peer Network Technologies
