Bitcoin's Mining Subsystem Highly Centralized With Nakamoto Coefficient of 2
Decentralization in blockchain networks involves distributing control and decision-making across a network of participants, rather than concentrating it in a single authority. This approach contrasts with centralized systems, where one entity manages everything. In decentralized blockchains, data is spread among nodes, with each node holding a copy of the ledger. This setup enhances transparency and reduces the risk of manipulation or system failure.
Decentralized networks offer several advantages, including enhanced security, transparency, and fault tolerance. Security is improved because decentralization reduces vulnerabilities associated with central points of attack. Transparency is fostered through the public recording of all transactions on a ledger accessible to all participants. Fault tolerance is achieved by distributing data across multiple nodes, ensuring the system remains operational even if some nodes fail.
However, decentralization is not a fixed state but rather a spectrum that shifts as network participation, governance structures, and consensus mechanisms evolve. The Nakamoto coefficient is a metric used to quantify the decentralization of a blockchain network. It represents the minimum number of independent entities, such as validators, miners, or node operators, that would need to collude to disrupt or compromise the network’s normal operation. This concept was introduced in 2017 by former CoinbaseCOIN-- chief technology officer Balaji Srinivasan and was named after Bitcoin's creator, Satoshi Nakamoto.
A higher Nakamoto coefficient indicates greater decentralization and security within the blockchain network. In such networks, control is more widely distributed among participants, making it more challenging for any small group to manipulate or attack the system. Conversely, a lower Nakamoto coefficient suggests fewer entities hold significant control, increasing the risk of centralization and potential vulnerabilities. For example, a blockchain with a Nakamoto coefficient of 1 would be highly centralized, as a single entity could control the network. In contrast, a network with a coefficient of 10 would require at least 10 independent entities to collude to exert control, reflecting a more decentralized and secure structureGPCR--.
Calculating the Nakamoto coefficient involves several key steps. First, identify the primary actors within the network, such as mining pools, validators, node operators, or stakeholders. Next, assess the extent of control each identified entity has over the network’s resources. For instance, in proof-of-work (PoW) blockchains like Bitcoin, this involves analyzing the hashrate distribution among mining pools. In proof-of-stake (PoS) systems, it requires examining the stake distribution among validators. Finally, rank the entities from highest to lowest based on their influence and cumulatively add their control percentages until the combined total exceeds 51%. The number of entities required to reach this threshold represents the Nakamoto coefficient.
For example, consider a PoW blockchain with the following mining pool distribution: Mining pool A with 25% of the total hashrate, Mining pool B with 20%, Mining pool C with 15%, Mining pool D with 10%, and others with 30%. To determine the Nakamoto coefficient, start with mining pool A (25%), add mining pool B (25% + 20% = 45%), and then add mining pool C (45% + 15% = 60%). In this scenario, the combined hashrate of mining pools A, B, and C reaches 60%, surpassing the 51% threshold. Therefore, the Nakamoto coefficient is 3, indicating that collusion among these three entities could compromise the network’s integrity.
Despite Bitcoin's reputation for decentralization, its mining subsystem is notably centralized. The Nakamoto coefficient is currently 2 for Bitcoin, meaning that just two mining pools control most of Bitcoin's mining power. This highlights the importance of the Nakamoto coefficient in assessing the decentralization of blockchain networks.
While the Nakamoto coefficient serves as a valuable metric for assessing blockchain decentralization, it possesses certain limitations that warrant careful consideration. The coefficient provides a static snapshot of decentralization, reflecting the minimum number of entities required to compromise a network at a specific point in time. However, blockchain networks are dynamic, with participant roles and influence evolving due to factors like staking, mining power shifts, or node participation changes. Consequently, the coefficient may not accurately capture these temporal fluctuations, potentially leading to outdated or misleading assessments.
Additionally, the Nakamoto coefficient typically focuses on specific subsystems, such as validators or mining pools, potentially overlooking other critical aspects of decentralization. Factors like client software diversity, geographical distribution of nodes, and token ownership concentration also significantly impact a network’s decentralization and security. Relying solely on the Nakamoto coefficient might result in an incomplete evaluation. Different blockchain networks employ various consensus mechanisms, each influencing decentralization differently. The Nakamoto coefficient may not uniformly apply across these diverse systems, necessitating tailored approaches for accurate measurement.
External factors, including regulatory actions, technological advancements, or market dynamics, can influence decentralization over time. For example, regulatory policies in specific regions might affect the operation of nodes or mining facilities, thereby altering the network’s decentralization landscape. The Nakamoto coefficient may not account for such externalities, limiting its comprehensiveness. To sum up, the Nakamoto coefficient is useful for assessing certain aspects of blockchain decentralization. It should be used alongside other metrics and qualitative assessments to gain a comprehensive understanding of a network’s decentralization and security.


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