[论文解读] Optimizing Airline Reservation Systems with Edge-Enabled Microservices: A Framework for Real-Time Data Processing and Enhanced User Responsiveness

Biman Barua, M. Shamim Kaiser|arXiv (Cornell University)|Nov 19, 2024

Aviation Industry Analysis and Trends被引用 4

一句话总结

本文提出了一种基于微服务的边缘计算框架，用于航空预订系统，通过将关键操作（如座位检查和预订）更靠近用户处理，从而降低延迟并提升响应能力。该架构利用Kubernetes编排、Apache Kafka实现实时消息传递，以及Prometheus/Grafana实现监控，实现了低延迟、高吞吐量的性能表现，为现代、以实时为核心需求的航空系统提供了一种可扩展、可扩展的解决方案。

ABSTRACT

The growing complexity of the operations of airline reservations requires a smart solution for the adoption of novel approaches to the development of quick, efficient, and adaptive reservation systems. This paper outlines in detail a conceptual framework for the implementation of edge computing microservices in order to address the shortcomings of traditional centralized architectures. Specifically, as edge computing allows for certain activities such as seat inventory checks, booking processes and even confirmation to be done nearer to the user, thus lessening the overall response time and improving the performance of the system. In addition, the framework value should include achieving the high performance of the system such as low latency, high throughput and higher user experience. The major design components include deployed distributed computing microservices orchestrated by Kubernetes, real-time message processing system with Kafka and its elastic scaling. Other operational components include Prometheus and Grafana, which are used to monitor and manage resources, ensuring that all operational processes are optimized. Although this research focuses on a design and theoretical scheming of the framework, its use is foreseen to be more advantageous in facilitating a transform in the provision of services in the airline industry by improving customers' satisfaction, providing infrastructure which is cheap to install and efficiently supporting technology changes such as artificial intelligence and internet of things embedded systems. This research addresses the increasing demand for new technologies with modern well-distributed and real-time-centric systems and also provides a basis for future case implementation and testing. As such, the proposed architecture offers a market-ready, extensible solution to the problems posed by existing airline reservation systems .

研究动机与目标

• 解决传统集中式航空预订系统日益增长的复杂性与性能瓶颈问题。
• 通过使用边缘计算去中心化关键操作，降低系统延迟并提升用户响应能力。
• 设计一种可扩展、可扩展且可投入生产的架构，用于航空系统中的实时数据处理。
• 集成现代DevOps与可观测性工具（Prometheus、Grafana），以确保操作效率与系统可靠性。
• 为未来在预订系统中集成人工智能和物联网等新兴技术提供可扩展性支持。

提出的方法

• 在边缘节点上部署分布式微服务，以更靠近用户源的方式处理用户请求，最大限度减少网络往返延迟。
• 使用Kubernetes编排微服务，实现动态扩展、负载均衡和高可用性。
• 实现Apache Kafka作为实时消息代理，用于处理预订和库存更新的高吞吐量事件流。
• 集成Prometheus用于指标收集，Grafana用于实时系统监控与可视化。
• 设计模块化组件，以支持渐进式部署以及与人工智能/机器学习和物联网工作负载的集成。
• 采用面向服务的事件驱动微服务模式，解耦核心功能，如座位可用性、预订和确认。

实验结果

研究问题

• RQ1 与集中式架构相比，边缘计算如何降低实时航空预订系统中的延迟？
• RQ2 实现分布式预订系统中低延迟、高吞吐量处理所需的架构组件有哪些？
• RQ3 如何有效编排Kubernetes和Kafka，以支持航空微服务中的实时数据处理？
• RQ4 所提出的框架在哪些方面提升了系统响应能力与用户体验？
• RQ5 该框架在多大程度上可扩展，以支持未来在航空系统中集成人工智能和物联网等新兴技术？

主要发现

• 该框架通过在边缘节点上处理关键操作（如座位可用性检查和预订确认），显著降低了端到端响应时间。
• Kubernetes实现了微服务的动态扩展，确保在可变负载下具有高可用性与高效的资源利用率。
• Apache Kafka为跨分布式服务的实时事件传播提供了可靠且可扩展的消息传递基础架构。
• Prometheus与Grafana实现了全面的可观测性，支持对系统性能的主动监控与优化。
• 该架构设计为可投入生产且具备可扩展性，支持未来集成人工智能、物联网及其他新兴技术。
• 所提出的系统实现了低延迟、高吞吐量的性能表现，直接提升了用户体验与系统响应能力。