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Empirical Performance Evaluation of ...
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Sondhi, Shiv.
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Empirical Performance Evaluation of Consensus Algorithms in Permissioned Blockchain Platforms.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Empirical Performance Evaluation of Consensus Algorithms in Permissioned Blockchain Platforms./
作者:
Sondhi, Shiv.
出版者:
Ann Arbor : ProQuest Dissertations & Theses, : 2021,
面頁冊數:
115 p.
附註:
Source: Masters Abstracts International, Volume: 83-03.
Contained By:
Masters Abstracts International83-03.
標題:
Computer science. -
電子資源:
https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28648874
ISBN:
9798538118120
Empirical Performance Evaluation of Consensus Algorithms in Permissioned Blockchain Platforms.
Sondhi, Shiv.
Empirical Performance Evaluation of Consensus Algorithms in Permissioned Blockchain Platforms.
- Ann Arbor : ProQuest Dissertations & Theses, 2021 - 115 p.
Source: Masters Abstracts International, Volume: 83-03.
Thesis (M.Sc.)--University of Windsor (Canada), 2021.
This item must not be sold to any third party vendors.
Over the past decade or so, blockchain and distributed ledger technology (DLT) have steadily made their way into the mainstream media. As a result, new blockchain platforms and protocols are emerging rapidly. However, the performance of the resultant systems and their resilience in hostile network environments is as yet not clearly understood. This thesis proposes a methodology to compare these platforms (specifically permissioned platforms) - and analyze the role of consensus protocols in determining system performance. It studies system performance in the face of network faults and varying loads and also provides a qualitative analysis of each shortlisted platform.The four platforms - Ethereum, Hyperledger Fabric, Hyperledger Sawtooth, and Cosmos-SDK - are shortlisted on the basis of the consensus protocols they offer, i.e. Clique, Raft, PBFT, and Tendermint respectively. The following chapters discuss our selection criteria, the performance metrics used for comparison, and the steps followed to build a blockchain application on each platform. Considering the prominence of modelling techniques in the existing literature, we build stochastic models for each shortlisted protocol and measure the same performance metrics as in our applications. Ultimately, this research aims to determine what factors affect the performance of blockchain systems, and what is the best way to measure their performance characteristics - by building applications or by building stochastic models?The experiments show that both methods of performance measurement have their pros and cons. They also highlight the importance of platform architecture in the determination of system performance. Selecting consensus protocols and blockchain platforms are critical decisions for any blockchain system. However, different choices shine in different settings. To recognize the best choice for a given use case, it is crucial to first compare the protocols - and this thesis does that on the basis of performance.
ISBN: 9798538118120Subjects--Topical Terms:
523869
Computer science.
Subjects--Index Terms:
Blockchain
Empirical Performance Evaluation of Consensus Algorithms in Permissioned Blockchain Platforms.
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Over the past decade or so, blockchain and distributed ledger technology (DLT) have steadily made their way into the mainstream media. As a result, new blockchain platforms and protocols are emerging rapidly. However, the performance of the resultant systems and their resilience in hostile network environments is as yet not clearly understood. This thesis proposes a methodology to compare these platforms (specifically permissioned platforms) - and analyze the role of consensus protocols in determining system performance. It studies system performance in the face of network faults and varying loads and also provides a qualitative analysis of each shortlisted platform.The four platforms - Ethereum, Hyperledger Fabric, Hyperledger Sawtooth, and Cosmos-SDK - are shortlisted on the basis of the consensus protocols they offer, i.e. Clique, Raft, PBFT, and Tendermint respectively. The following chapters discuss our selection criteria, the performance metrics used for comparison, and the steps followed to build a blockchain application on each platform. Considering the prominence of modelling techniques in the existing literature, we build stochastic models for each shortlisted protocol and measure the same performance metrics as in our applications. Ultimately, this research aims to determine what factors affect the performance of blockchain systems, and what is the best way to measure their performance characteristics - by building applications or by building stochastic models?The experiments show that both methods of performance measurement have their pros and cons. They also highlight the importance of platform architecture in the determination of system performance. Selecting consensus protocols and blockchain platforms are critical decisions for any blockchain system. However, different choices shine in different settings. To recognize the best choice for a given use case, it is crucial to first compare the protocols - and this thesis does that on the basis of performance.
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https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28648874
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