Dynamic Evolution Method and Symmetric Consistency Analysis for Big Data-Oriented Software Architecture Based on Extended Bigraph

With the development of artificial intelligence technology, there are increasingly high requirements for processing big data systems. Big data systems have undergone rapid evolution in response to changing demands. Due to the complex structural connections and dispersed component positions of big data processing systems, traditional formal methods find it difficult to dynamically model their structure and position simultaneously. To address this issue, this study proposes a formal modeling framework that extends Bigraph to support the dynamic evolution of big data software architecture. This model is capable of verifying the symmetry consistency of structural connections and component positions in evolutionary systems and evaluating them through real-life case studies of banking big data systems. The results confirmed its correctness and practical feasibility.

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Publication Details

Journal
Symmetry
Published
2025-04-21
DOI
https://doi.org/10.3390/sym17040626
Citations
1
Primary Topic
Software System Performance and Reliability
Type
article
Field-Weighted Citation Impact
1.49

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article

Dynamic Evolution Method and Symmetric Consistency Analysis for Big Data-Oriented Software Architecture Based on Extended Bigraph

Qifeng Zou, Chaoze Lu
1 citations
Symmetry
Software System Performance and Reliability
1.49
article

Dynamic Evolution Method and Symmetric Consistency Analysis for Big Data-Oriented Software Architecture Based on Extended Bigraph

Qifeng Zou, Chaoze Lu
article en
1 citations

Abstract

With the development of artificial intelligence technology, there are increasingly high requirements for processing big data systems. Big data systems have undergone rapid evolution in response to changing demands. Due to the complex structural connections and dispersed component positions of big data processing systems, traditional formal methods find it difficult to dynamically model their structure and position simultaneously. To address this issue, this study proposes a formal modeling framework that extends Bigraph to support the dynamic evolution of big data software architecture. This model is capable of verifying the symmetry consistency of structural connections and component positions in evolutionary systems and evaluating them through real-life case studies of banking big data systems. The results confirmed its correctness and practical feasibility.

SymmetryVol. 17(4)
Ningbo University (CN), Ningbo University of Technology (CN)
National Natural Science Foundation of China, Ningbo University, Ningbo University of Technology, Natural Science Foundation of Ningbo, Natural Science Foundation of Zhejiang Province
Openalex Percentile: Top 18%
Software System Performance and Reliability
1.49
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