Multi-channel data flow software fault detection for social internet of things with system assurance concerns

Ling You ()
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Ling You: Information Engineering College of Yango University

International Journal of System Assurance Engineering and Management, 2023, vol. 14, issue 1, No 33, 472-482

Abstract: Abstract During application development, various unknown factors can affect the application and cause failures. According to the traditional software engineering techniques, software testing is usually performed later in software development, and it is difficult to find and correct these failures at this time. More and more distributed software systems are deployed on public cloud computing platforms and use the Internet to provide services outward. The complexity, dynamics, and openness of cloud computing environments make distributed software systems more prone to failure, which can result in service failures that can affect the normal use of large numbers of users. Therefore, in this paper, we study the fault detection algorithm of multi-channel parallel data flow software based on cloud computing. The data fusion and clustering models are integrated to detect the data features with the numerical verification, and the theoretical framework is also assigned to a better robustness for the theoretical framework implementation. The final results are also validated through the systematic overview. Future research directions are also included in the conclusion.

Keywords: Cloud computing; Social internet of things; Data flow software; Fault detection; Ubiquitous clouds; System assurance (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s13198-023-01878-4

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