Cluster-Based Classification of Blockchain Consensus Algorithms
Keywords:Blockchain, Cluster-based classification, Consensus algorithms, Proof of Work, Spearman Rank Correlation, Ward Method
In recent years, Blockchain has become a disruptive technology to protect the integrity of information, especially in open and collaborative information systems. Its main advantage is the possibility to reach consensus on the new data blocks to be added to the chain, even with anonymous actors. The most common consensus mechanism is Proof of Work, but it has been proven to be very inefficient in terms of energy spent by the members of the blockchain. In the literature there are many other techniques that pretend to become the new popular mechanism. However, the number is increasing too fast to really be able to differentiate among all the options. In this work, a new characterization of consensus algorithm is proposed, than can be used to find families of mechanism using cluster-based classification. Using the Ward Method and Spearman’s Rank Correlation analysis, new clusters of consensus mechanisms were identified. The results describe the behavioral patterns not seen before in the literature. In addition, some open problems of current consensus algorithms are discussed.