Decision-making method in interdependent computing systems
Вантажиться...
Дата
2025
Назва журналу
Номер ISSN
Назва тому
Видавець
Хмельницький національний університет
Анотація
The relevance of this paper lies in the fact that modern interdependent computing systems are being actively implemented in critical areas ranging from smart energy grids and transportation systems to autonomous robotic platforms and distributed cloud services. These systems are characterized by a complex structure, a large number of interacting agents, and high
requirements for real-time decision-making. Despite significant scientific and technological progress, a number of challenges remain unresolved to ensure the sustainability, adaptability, and coherence of all system components.
One of the key challenges is the need to ensure rational decision-making in a decentralized environment where each agent has limited information about the state of the system as a whole and operates under conditions of uncertainty and potential distrust of other agents. Classical centralized methods are often ineffective or inapplicable in such cases due to excessive complexity or delays in data exchange.
The issue of developing methods that ensure not only the correctness of decisions but also compliance with time constraints is particularly relevant. In interdependent computing environments, where the decision of one agent affects the outcome of the work of others, any delay or error in the strategy can lead to degradation of the performance of the entire system.
In such environments, it is crucial to use adaptive, game-based, and reputation-based approaches that allow for dynamic
consistency and stability of the system.
In this paper, we develop a decision-making method for interdependent computing systems that combines Bayesian reputation updating, log-linear strategy learning, and reinforcement learning mechanisms. The peculiarity of the proposed method is its ability to adapt to changes in the environment and effectively detect unscrupulous agents by dynamically adjusting reputations. The algorithmic implementation of the model allows achieving the Bayesian-Nash equilibrium, which indicates the stability of the system even in complex interaction scenarios.
The results of experimental modeling have demonstrated that the proposed method strikes a balance between
adaptability, reliability, and efficiency of interactions. The system demonstrates the ability to self-organize, stabilizes in fewer
iterations compared to classical approaches, and effectively prevents the influence of sabotaging behavior of individual agents.
The prospect of further research is to adapt the model to different types of computing environments, including MEC
infrastructures, edge systems, and IoT platforms. Special attention is planned to be paid to the development of new objective
functions that would take into account not only the stability and speed of convergence, but also energy consumption, network bandwidth, and quality of service (QoS).
Опис
Ключові слова
modern interdependent computing systems, rational decision-making, decision-making method for interdependent computing systems, the Bayesian-Nash equilibrium
Бібліографічний опис
Kryzhanyvskyi D. Decision-making method in interdependent computing systems / D. Kryzhanyvskyi, A. Drozd, O. Besedovskyi // Computer Systems and Information Technologies. – 2025. – № 1. – P. 54-65.