A Network-gene-mutation-based model for large network dynamic application reliability evaluation

Xiangyu Zheng, Ning Huang and Zhiwei Yi

Journal of Risk and Reliability, 2024, vol. 238, issue 6, 1103-1117

Abstract: Network evolution model (NEM) is a framework proposed recently for dynamic application reliability evaluation which integrates various factors that affect application failure. The existing component-based NEM relies on an exhaustive enumeration of all potential states of network components, which can lead to a computational bottleneck, especially when dealing with large networks. Therefore, to tackle this challenge, this paper presents a Network-gene-mutation-based NEM. The model introduces novel concepts of Network-cells and Network-genes inspired by the gene-cell-function model framework used in system biology to address complex disease problems. Network-cells are constructed according to the statistical classification of components. Network-genes are constructed by the average failure rate of components within a Network-cell. Dynamic network states are simulated by the Network-gene-mutation function of Network-cells instead of the failure and repair function of network components. Validation of our proposed model is performed through the comparison with benchmark models. The results demonstrate the validity of our proposed model in calculating dynamic application reliability. Besides, the comparison results with the component-based NEM also suggest that our proposed model reduces the time complexity of the algorithm from square order O ( n 2 ) to constant order O ( 1 ) and improves the simulation efficiency by roughly 10 4 . Applied to networks of varying scales, our proposed model proves to be an efficient method for calculating dynamic application reliability in large networks. In summary, this paper offers a promising solution to address the computational bottlenecks encountered in the component-based NEM when evaluating the reliability of dynamic applications.

Keywords: Network evolution model; Application reliability; Network-cell; Network-gene; Gene mutation (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/1748006X231209029 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:risrel:v:238:y:2024:i:6:p:1103-1117

DOI: 10.1177/1748006X231209029

Access Statistics for this article

More articles in Journal of Risk and Reliability
Bibliographic data for series maintained by SAGE Publications ().