ALGORITHMIC OPTIMIZATION IN DISTRIBUTED COMPUTING SYSTEMS FOR ENHANCING THE STABILITY AND EFFICIENCY OF SCALABLE DIGITAL PLATFORMS

<p>The article examines the problem of algorithmic optimization in distributed computational systems as a key factor in enhancing the stability and efficiency of scalable digital platforms. It analyzes contemporary models, including quorum protocols, consensus algorithms, load balancing methods, scheduling strategies, and graph computations, all adapted to environments characterized by high dynamism, asynchrony, and partial failures. The study highlights the practical implementation of these solutions in the infrastructures of leading technology companies such as Google, Amazon, and Microsoft, where system resilience is achieved not through resource overprovisioning, but through intelligent management of computational processes. The article emphasizes the critical role of algorithmic strategies in enabling fault-tolerant and adaptive distributed platforms. </p>