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Consensus Algorithm

  • Rashmi BhardwajEmail author
  • Debabrata Datta
Chapter
  • 27 Downloads
Part of the Studies in Big Data book series (SBD, volume 71)

Abstract

Consensus algorithm in general is framed as a decision-making process where a group of people express their individual opinions to construct the decision which provides a best estimate of a process or system. Each member of the group expresses their opinion to support the decisions taken for a course of action. In simple terms, it is just a method to decide any event to occur within a group. Every one present in the group can suggest an idea, but the majority will be in favor of the one that helps them the most. Others have to deal with this decision whether they liked it or not. Byzantine Fault Tolerance (BFT), a problem of Byzantine General, is a system with a particular event of failure. One can experience best the aforementioned situation (BFT) with a distributed computer system. Many times, there can be malfunctioning consensus systems. These components are responsible for the further conflicting information. Consensus systems can only work successfully if all the elements work in harmony. However, if even one of the components in this system malfunctions the whole system could break down. These Blockchain consensus models are just the way to reach an agreement. However, there can’t be any decentralized system without common consensus algorithms. It won’t even matter whether the nodes trust each other or not. They will have to go by certain principles and reach a collective agreement. In order to do that, it is required to check out all the Consensus algorithms. It can be stated that versatility of blockchain networks is due to consensus algorithms. However, blockchain consensus algorithm may have pros and cons which can always alter the perfection of the algorithm.

Keywords

Consensus Algorithm (CA) Artificial Intelligence (AI) Cognitive Intelligence (CI) Human Intelligence (HI) Blockchain Peer-to-peer network (P2P) 

Notes

Acknowledgements

Authors are thankful to Guru Gobind Singh Indraprastha University and Bhabha Atomic Research Centre for research facility.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Nonlinear Dynamics Research LabUniversity School of Basic & Applied Sciences, Guru Gobind Singh Indraprastha UniversityDelhiIndia
  2. 2.Radiological Physics & Advisory DivisionBhabha Atomic Research CentreMumbaiIndia

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