Related papers: Real-Time Performance Optimization of Travel Reser…
The paper presents a framework of microservices-based architecture dedicated to enhancing the performance of real-time travel reservation systems using the power of predictive analytics. Traditional monolithic systems are bad at scaling and…
The objective of this research is how an implementation of AI algorithms in the microservices architecture enhances travel itineraries by cost, time, user preferences, and environmental sustainability. It uses machine learning models for…
This paper investigates the inclusion of microservices architecture in the development of scalable and reliable airline reservation systems. Most of the traditional reservation systems are very rigid and centralized which makes them prone…
This research investigates the implementation of a real-time, microservices-oriented dynamic pricing system for the travel sector. The system is designed to address factors such as demand, competitor pricing, and other external…
This paper introduces a microservices architecture for the purpose of enhancing the flexibility and performance of an airline reservation system. The architectural design incorporates Redis cache technologies, two different messaging…
The increasing demand for scalable, efficient resource management in hybrid cloud environments has led to the exploration of AI-driven approaches for dynamic resource allocation. This paper presents an AI-driven framework for resource…
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…
This paper proposes a reinforcement learning-based method for microservice resource scheduling and optimization, aiming to address issues such as uneven resource allocation, high latency, and insufficient throughput in traditional…
Trip planning for intelligent vehicles increasingly requires selecting optimal routes rather than merely producing feasible itineraries, as interacting factors such as travel time, energy consumption, and traffic conditions directly affect…
Artificial Intelligence (AI) and machine learning have been increasingly adopted for travel demand forecasting. The AI-based travel demand forecasting models, though generate accurate predictions, may produce prediction biases and raise…
Artificial Intelligence (AI) has been improving the performance of systems for a diverse set of tasks and introduced a more interactive generation of personal agents. Despite the current trend of applying AI for a great amount of areas, we…
In the last few years, the cloudification of applications requires new concepts and techniques to fully reap the benefits of the new computing paradigm. Among them, the microservices architectural style, which is inspired by…
With the maturity of web services, containers, and cloud computing technologies, large services in traditional systems (e.g. the computation services of machine learning and artificial intelligence) are gradually being broken down into many…
Advance reservation is important to guarantee the quality of services of jobs by allowing exclusive access to resources over a defined time interval on resources. It is a challenge for the scheduler to organize available resources…
We study a fundamental model of resource allocation in which a finite number of resources must be assigned in an online manner to a heterogeneous stream of customers. The customers arrive randomly over time according to known stochastic…
This article examines the characteristics of human errors in processing transportation requests. The role of artificial intelligence (AI) in maritime transportation is explored. The main methods and technologies used for automating and…
Large language models and AI agents have recently shown promise in automating software performance optimization, but existing approaches predominantly rely on local, syntax-driven code transformations. This limits their ability to reason…
We propose AI-CARGO, a revenue management system for air-cargo that combines machine learning prediction with decision-making using mathematical optimization methods. AI-CARGO addresses a problem that is unique to the air-cargo business,…
This paper considers the dispatching of large-scale real-time ride-sharing systems to address congestion issues faced by many cities. The goal is to serve all customers (service guarantees) with a small number of vehicles while minimizing…
The use of AI in microservices (MSs) is an emerging field as indicated by a substantial number of surveys. However these surveys focus on a specific problem using specific AI techniques, therefore not fully capturing the growth of research…