Integral survivability metric of an information system on a mobile platform under functional cascading and secondary failures
DOI:
https://doi.org/10.30837/2522-9818.2025.4.078Keywords:
integrated metric; survivability; information system; cascading fault; risk-oriented monitoring.Abstract
The subject of the study is an integral metric of the survivability of an information system on a mobile platform under intermittent connectivity, partial observability, and cascading and secondary failures. The system is presented as a multilevel "data–processes–resources" structure. The goal of the work is to develop an integrated survivability metric that takes into account time deviations from requirements, their propagation through a dependency graph, and hidden violations; to propose a single-pass algorithm and prove its properties on scenarios. The article solves the following tasks: to formalize service requirements and structure projection; to build a metric with risk-oriented aggregation of deficits, cascading correction, and systematic consideration of secondary failures; to develop single-pass calculations in "availability windows"; to prove monotonicity, scale invariance, and resistance to omissions; to define rules for parameter tuning and configuration comparison; to perform experimental verification and comparison with baseline indicators. The following methods are used: projection of services at the level of data, processes, and resources; use of conditional average excess as risk-oriented aggregation; cascading correction by depth and width; organization of secondary failures and desynchronization fixation; normalization in "availability windows"; single-pass updates close to linear complexity. The following results were obtained: an integrated metric of survivability was proposed and formally defined; its monotonicity in terms of parameters, boundedness, invariance to scaling, and resistance to omissions were proven; the difference from the average deficit was shown – the proposed metric amplifies the contribution of rare deep failures and responds to cascading, while the average values are almost constant; in the absence of service deficits, a positive level is maintained due to the detection of latent secondary failures; scenarios yield consistent families of curves and a three-dimensional surface that demonstrate controllable sensitivity tuning and stable ranking of configurations for industrial mobile platform operating conditions. Conclusions: The proposed metric provides a service-consistent assessment of the state of the information system, while taking into account time deficits, cascading propagation, and secondary failures. It is suitable for sequential computing in resource-constrained environments, enhances early risk detection, and supports monitoring, localization, and survivability.
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