Blockchain-Based Trust and Transparency in Airline Reservation Systems using Microservices Architecture
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Abstract (arXiv)
This research gives a detailed analysis of the application of blockchain technology to the airline reservation systems in order to bolster trust, transparency, and operational efficiency by overcoming several challenges including customer control and data integrity issues. The study investigates the major components of blockchain technology such as decentralised databases, permanent records of transactions and transactional clauses executed via codes of programs and their impacts on automated systems and real-time tracking of audits. The results show a 30% decrease in booking variations together with greater data synchronization as a result of consensus processes and resistant data formations. The approach to the implementation of a blockchain technology for the purpose of this paper includes many APIs for the automatic multi-faceted record-keeping system including the smart contract execution and controllable end-users approach. Smart contracts organized the processes improving the cycle times by 40% on the average while guaranteeing no breach of agreements. In addition to this, the architecture of the system has no single point failure with over 98% reliability while measures taken to improve security have led to 85% of the customers expressing trust in the services provided. In summation, the results suggest that reservations in the airline sector stand a chance of being redefined with blockchain through savoring the benefits of a single source of truth while attempting to resolve this intrinsic problem of overcomplexity. Although the system improves the experience of customers and the level of operational transparency, issues concerning scalability and regulatory adherence. This research is also a stepping stone for further studies that are intended to address these challenges and more applicable to the airline industry.
Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). First posted on arXiv 18 Oct 2024.
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Citing papers per year: 2024: 6.
6 papers.
- 2024Optimizing Travel Itineraries with AI Algorithms in a Microservices Architecture: Balancing Cost, Time, Preferences, and Sustainabilitycited by 5
- 2024Enhancing Resilience and Scalability in Travel Booking Systems: A Microservices Approach to Fault Tolerance, Load Balancing, and Service Discoverycited by 4
- 2024Novel Architecture for Distributed Travel Data Integration and Service Provision Using Microservicescited by 3
- 2024Leveraging Microservices Architecture for Dynamic Pricing in the Travel Industry: Algorithms, Scalability, and Impact on Revenue and Customer Satisfactioncited by 2
- 2024A Next-Generation Approach to Airline Reservations: Integrating Cloud Microservices with AI and Blockchain for Enhanced Operational Performancecited by 1
- 2024Optimizing Airline Reservation Systems with Edge-Enabled Microservices: A Framework for Real-Time Data Processing and Enhanced User Responsivenesscited by 0
- 2024Optimizing Airline Reservation Systems with Edge-Enabled Microservices: A Framework for Real-Time Data Processing and Enhanced User Responsiveness19 Nov 2024
- 2024A Next-Generation Approach to Airline Reservations: Integrating Cloud Microservices with AI and Blockchain for Enhanced Operational Performance10 Nov 2024
- 2024Leveraging Microservices Architecture for Dynamic Pricing in the Travel Industry: Algorithms, Scalability, and Impact on Revenue and Customer Satisfaction3 Nov 2024
- 2024Novel Architecture for Distributed Travel Data Integration and Service Provision Using Microservices31 Oct 2024
- 2024Enhancing Resilience and Scalability in Travel Booking Systems: A Microservices Approach to Fault Tolerance, Load Balancing, and Service Discovery25 Oct 2024
- 2024Optimizing Travel Itineraries with AI Algorithms in a Microservices Architecture: Balancing Cost, Time, Preferences, and Sustainability23 Oct 2024