(untitled) (DIGITAL TRANSFORMATION AND ARTIFICIAL INTELLIGENCE, 2025)
Efficient request distribution is one of the important factors for the stable and uninterrupted operation of modern information systems. In the context of increasing cloud computing, real-time services and multi-user environments, traditional distribution algorithms (e.g. Round Robin, Least Connection, Weighted Response Time) are losing their effectiveness due to insufficient consideration of uncertainty and dynamic changes in server state. In this context, there is a growing need for decision-making systems based on adaptive and state-sensitive approaches. Fuzzy logic-based models have a significant advantage in representing uncertainties in real-world environments, especially due to the ability to estimate system parameters through linguistic variables. However, the effectiveness of these systems directly depends on the shape and parameters of the membership functions, i.e. their semantic relevance and sensitivity. Using membership functions of the same shape for each linguistic value (for example, only a triangle) can reduce the accuracy of the system’s decision-making.