Cluster-Based Classification of Blockchain Consensus Algorithms

Fredy Aponte, Luz Gutierrez, Madga Pineda, Ines Merino, Augusto Salazar, Pedro Wightman

Research output: Contribution to journalArticlepeer-review

Abstract

In recent years, Blockchain has become a disruptivetechnology to protect the integrity of information, especially inopen and collaborative information systems. Its main advantageis the possibility to reach consensus on the new data blocks tobe added to the chain, even with anonymous actors. The mostcommon consensus mechanism is Proof of Work, but it has beenproven to be very inefficient in terms of energy spent by themembers of the blockchain. In the literature there are many othertechniques that pretend to become the new popular mechanism.However, the number of this techniques is growing too fast toreally be able to differentiate among all the options. In this work,a new characterization of consensus algorithm is proposed, thatcan be used to find families of mechanism using cluster-basedclassification. Using the Ward Method and Spearmans RankCorrelation analysis, new clusters of consensus mechanisms wereidentified. The results describe the behavioral patterns not seenbefore in the literature. In addition, some open problems ofcurrent consensus algorithms are discussed.

Original languageEnglish (US)
Article number9448552
Pages (from-to)688-696
Number of pages9
JournalIEEE Latin America Transactions
Volume19
Issue number4
DOIs
StatePublished - Apr 2021
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Electrical and Electronic Engineering

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