NEW METHODS OF TRAFFIC DISTRIBUTION ON THE PERFORMANCE OF MODERN CLOUD PLATFORMS

Abstract

This article addresses the issue of the impact of new traffic distribution methods on the performance of modern cloud platforms. Specifically, the authors explore cutting-edge approaches to traffic routing optimization that significantly reduce latency, improve resource utilization, and enhance the overall performance of cloud infrastructures. The study analyzes various load-balancing algorithms, traffic routing strategies, and adaptive resource management techniques in the context of changing load and bandwidth requirements. The main goal of the research is to assess the impact of new traffic distribution methods on cloud platform efficiency and to develop mathematical models for performance evaluation and improvement. To achieve this, simulation experiments were conducted using different cloud infrastructure models, allowing a comparison between traditional methods and new optimization approaches. The study's results demonstrated a significant reduction in latency (up to 30-40%) using the new methods, as well as improvements in resource utilization and reduction of congestion in cloud systems. The practical application of these methods enables cloud service providers to enhance service quality and ensure high user satisfaction significantly. The potential for integrating artificial intelligence and machine learning for further refinement of traffic management systems and adaptation to changing conditions is also highlighted.