Systematic performance evaluation using component-in-the-loop approach

Kocsis, Imre; Klenik, Attila; Pataricza, András; Telek, Miklós; Deé, Flórián; Cseh, D.

doi:10.1504/ijcc.2018.095401

Cited by 5 publications

(4 citation statements)

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“…The endorsement phase of HLF consensus is particularly important in HLF performance engineering [12]. We have created an ontology refinement to describe the endorsement phase of HLF consensus (including end-to-end transaction processing), represented as hierarchical sequential parallel activities from [4].…”

Section: B Extensions For Endorsement Visual Analyticsmentioning

confidence: 99%

Knowledge-driven Exploratory Performance Data Analysis for Execute-Order-Validate Blockchains

Al-Gburi¹,

Kocsis²

2023

Proceedings of the 30th Minisymposium

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Exploratory data analysis (EDA) of the performance characteristics of complex IT systems, such as enterprise blockchain solutions, would significantly benefit from explicit representations of, and inference on knowledge about the analyzed system. However, connecting EDA and knowledge representation is not part of the current practice. As a novel approach, this paper presents a generic hierarchical activity ontology, connected to Hyperledger Fabric experiments with end-to-end delay, endorsement delay, ordering delay, and block validation observations. On this basis, we present rules for inferring knowledge-based visualization declarations on this ontology. Lastly, we generate Jupyter notebooks for the inferred sequence of visualizations.

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Section: B Extensions For Endorsement Visual Analyticsmentioning

confidence: 99%

Knowledge-driven Exploratory Performance Data Analysis for Execute-Order-Validate Blockchains

Al-Gburi¹,

Kocsis²

2023

Proceedings of the 30th Minisymposium

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“…Figure 1: Typical performance evaluation steps data acquisition; representation; analysis; visualization and reporting -with a proper model-driven engineering (MDE) support. Different performance analysis tasks -such as bottleneck identification and latency anomaly root cause analysis -can be considered domain-specific refinements [28] of the analysis step, defining further, embedded sub-workflows. However, the technical metrology of performance evaluation poses specific challenges.…”

Section: Measurement Data Analysismentioning

confidence: 99%

Adding Semantics to Measurements

Klenik

Pataricza

2022

Acta Cybern

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The design and operation of modern software systems exhibit a shift towards virtualization, containerization and service-based orchestration. Performance capacity engineering and resource utilization tuning become priority requirements in such environments. Measurement-based performance evaluation is the cornerstone of capacity engineering and designing for performance. Moreover, the increasing complexity of systems necessitates rigorous performance analysis approaches. However, empirical performance analysis lacks sophisticated model-based support similar to the functional design of the system. The paper proposes an ontology-based approach for facilitating and guiding the empirical evaluation throughout its various steps. Hyperledger Fabric (HLF), an open-source blockchain platform by the Linux Foundation, is modelled and evaluated as a pilot example of the approach, using the standard TPC-C performance benchmark workload.

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“…A comparative study has been developed on the offering of a solution to security concerns through a trusted third party (Singh & Lee, 2017). The implementation of the technology applied to various complex systems enables the firms to evaluate the performance outcome attempting to venture into the novelty on the hyper ledger fabric services (Kocsis et al , 2018). Experiments were conducted to confirm the secured and shared transactions that can also facilitate useful trades by various players in the market based on the Paillier cryptosystem to assure the confidentiality of data sharing (Zhang, White, Schmidt, Lenz, & Rosenbloom, 2018).…”

Section: Theoretical Backgroundmentioning

confidence: 99%

Blockchain: an EOM approach to reconciliation in banking

Vedapradha¹,

Ravi

2021

INMR

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PurposeThe study aim is to evaluate the contribution of Blockchain technology (Cryptobanking) using expected operating model (EOM) to address the pain points in reconciliation at middle and back-office operational levels in assessing the significance of this technology on return on investment.Design/methodology/approachA structured questionnaire was designed to collect primary data using a stratified sampling method from 120 respondents working in leading Investment banks operating in the geographical locality of urban Bangalore. Demographic variables, accounting variables, data reporting variables, approach variables, variables of EOM were considered to validate the hypothesis with the help of statistical tools, namely ANOVA, and Multiple Stepwise Regression Analysis.FindingsThe results obtained confirm that there is significant difference in reconciliation with implementation of an innovative business process. Financial analysis is the highest predictor of ROI when integrated with technology as the adapted Blockchain innovation in reconciliation is the most influencing factor in enhancing, improving ROI playing a pivotal role in the Investment banks.Originality/valueBlockchain technology (Cryptobanking) facilitates in transforming the reconciliation process of these banks with improved operational efficiency. Blockchain and settlement platforms offer inter-organization solutions facilitating in the reconciliation of various transactions in real-time through a trust-based network in the form of digital settlements with better consortiums.

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Systematic performance evaluation using component-in-the-loop approach

Cited by 5 publications

References 0 publications

Knowledge-driven Exploratory Performance Data Analysis for Execute-Order-Validate Blockchains

Knowledge-driven Exploratory Performance Data Analysis for Execute-Order-Validate Blockchains

Adding Semantics to Measurements

Blockchain: an EOM approach to reconciliation in banking

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