Date of Award

4-9-2020

Publication Type

Master Thesis

Degree Name

M.Sc.

Department

Computer Science

First Advisor

Saeed Samet

Keywords

Blockchains, Byzantine Fault Tolerance, Consensus Algorithms, Cryptograpgy, Decentralized Computing, Distributed Ledger

Rights

info:eu-repo/semantics/openAccess

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Abstract

Blockchain technology has redefined the way the software industry's core mechanisms operate. With recent generations of improvement observed in blockchain, the industry is surging ahead towards replacing the existing computing paradigms with consortium blockchain-enabled solutions. For this, there is much research observed which aims to make blockchain technology’s performance at par with existing systems. Most of the research involves the optimization of the consensus algorithms that govern the system. One of the major aspects of upcoming iterations in blockchain technology is making individual consortium blockchains collaborate with other consortium blockchains to validate operations on a common set of data shared among the systems. The traditional approach involves requiring all the organizations to run the consensus and validate the change. This approach is computationally expensive and reduces the modularity of the system. Also, the optimized consensus algorithms have their specific requirements and assumptions which if extended to all the organizations leads to a cluttered system with high magnitudes of dependencies.This thesis proposes an architecture that leverages the use of state machine replication extended to all the nodes of different organizations with seamless updates over a random graph network without involving all the nodes participating in the consensus. This also enables organizations to run their respective consensus algorithms depending on their requirements. This approach guarantees the finality of consistent data updates with reduced computations with high magnitudes of scalability and flexibility.

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