Smart OS resource scheduling using AI for Railway Reservations

Abstract Millions of passenger’s book tickets daily, making railway reservation systems critical for managing all passenger data. The system experiences high traffic while booking Tatkal tickets during peak hours. This leads to slow response transactions and failures. Sometimes servers get crashed. This is due to the insufficient allocations of OS resources, like CPU, memory, storage, and N/W bandwidth.[5] Traditional operating system scheduling methods like FCFS and round robin are not adopted dynamically for sudden increasing demand that causes poor system performance [4]. “Smart OS resource scheduling system using AI" Overcome these challenges by analyzing booking patterns. Real-time user request AI models help to predict peak load, and according to this load, the AI model dynamically prioritises tasks.The system organises the allocation of CPU, memory, and storage resources to handle the critical operation of payment processing, and the seat confirmation AI model is used. The AI model allocates the seats effectively by forecasting the passenger demand and adjusting reservations dynamically. The advanced AI system improves the stability, minimises the failure, and reduces the waiting time.AI-driven operating system resource scheduling explains how intelligent computing transforms the large-scale reservation system into one that is more reliable and responsive to users.