A SCALABLE RELIABILITY ESTIMATION ALGORITHM FOR COMPLEX COMPUTER NETWORKS UNDER DYNAMIC CONDITIONS WITH AI-BASED EXTENSIONS
DOI:
https://doi.org/10.68302/std2026.vol3.139Keywords:
Computer networks, AI, Information analysis, Risky technical devicesAbstract
This scientific article proposes a modern mathematical algorithm designed to improve workflow and enhance the efficiency of reliability assessment in computer networks. The primary objective of the research is to develop an advanced method for predicting and analysing potential failures in complex computer environments. The proposed algorithm incorporates contemporary modelling approaches, innovative optimization techniques and information flow analysis to enable improved planning and resource allocation, while significantly reducing downtime and repair interventions in critical computer-based technical systems. The obtained results demonstrate the applicability of the proposed algorithm across a broad spectrum of sectors, including both industrial and educational domains involving computer devices. Specifically, it is applicable in areas where the reliability of computer and network infrastructure plays a key role in maintaining high levels of operational productivity and technical safety. Additionally, elements of artificial intelligence are introduced as a supplementary component to enhance adaptability and support predictive analysis under dynamic conditions.
Supporting Agencies
In this section of our scientific article, we would like to sincerely thank all our colleagues from the department for their support, valuable advice, motivation, and cooperation. The completion of this research paper would not have been possible without their professional contribution and helpful recommendations. We would also like to express our heartfelt gratitude to our families for their inspiring presence, constant support and patience, which motivated and encouraged us to keep moving forward. Additionally, we would like to acknowledge our student Ilker Hatib for his dedication, committed time, and empathy throughout the entire research process. This publication is funded by the fund "Support for Publishing Publications in Journals with Impact Factor (IF) and Impact Rank (SJR)" of Konstantin Preslavsky University of Shumen, Republic of Bulgaria.Downloads
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Copyright (c) 2026 Silvia Nikolova, Daniel Denev
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