A Next-Generation Approach to Airline Reservations: Integrating Cloud Microservices with AI and Blockchain for Enhanced Operational Performance

TL;DR

This paper introduces a next-generation airline reservation system integrating cloud microservices, AI, and blockchain to significantly improve efficiency, security, and customer engagement, demonstrating notable performance enhancements over traditional systems.

Contribution

The paper presents a novel modular architecture combining cloud microservices, AI, and blockchain for airline reservations, achieving higher availability, scalability, and security compared to conventional systems.

Findings

System availability increased by 30%

Customer engagement improved by 25%

Transaction speed and security enhanced by 35% and 15% respectively

Abstract

This research proposes the development of a next generation airline reservation system that incorporates the Cloud microservices, distributed artificial intelligence modules and the blockchain technology to improve on the efficiency, safety and customer satisfaction. The traditional reservation systems encounter issues related to the expansion of the systems, the integrity of the data provided and the level of service offered to the customers, which is the main focus of this architecture through the modular and data centric design approaches. This will allow different operations such as reservations, payments, and customer data management among others to be performed separately thereby facilitating high availability of the system by 30% and enhancing performance of the system by 40% on its scalability. Such systems contain AI driven modules that utilize the past booking patterns along with the profile of the customer to estimate the demand and make recommendations, which increases to 25 % of customer engagement. Moreover, blockchain is effective in engaging an incorruptible ledger system for the all transactions therefore mitigating fraud incidences and increasing the clarity by 20%. The system was subjected to analysis using a simulator and using machine learning evaluations that rated it against other conventional systems. The results show that there were clear enhancements in the speed of transactions where the rates of secure data processing rose by 35%, and the system response time by 15 %. The system can also be used for other high transaction industries like logistics and hospitality. This structural design is indicative of how the use of advanced technologies will revolutionize the airline reservation sector. The implications are growing effectiveness, improvement in security and greater customer contentment.