Distributed Cloud System for Real-Time Travel Planning
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Solution Overview
Problem
Current distributed Internet service models and cloud computing systems face challenges in providing stable real-time performance and reliability under high volumes of customer inquiries and transactions, particularly in complex systems like railway e-ticketing and travel planning, where scalability, security, and flexibility are essential.
Innovation Solution
A distributed cloud computer system that uses a multidimensional value model to process user inputs in real-time, receiving information from various sources, categorizing and updating event values, and presenting personalized recommendations based on user selections, while synchronizing data across a network to ensure efficient e-commerce transactions and travel planning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If a centralized cloud server is used to handle all customer inquiries and transactions, then data consistency and centralized control are improved, but real-time performance and system reliability deteriorate under high volumes of requests
Solution Approach 1:
The patent divides the centralized cloud service into multiple distributed edge servers deployed across different geographic locations. Each edge server handles local requests independently, segmenting the monolithic centralized system into smaller autonomous units that can operate concurrently, thereby improving system reliability under high request volumes while maintaining data consistency through synchronization protocols.
Solution Approach 2:
The patent introduces a service mesh architecture as an intermediary layer between edge servers and customers. This service mesh manages service-to-service communication, handles routing, and coordinates data synchronization, acting as a mediator that maintains data consistency across distributed edge servers while preserving their independence and reliability.
2Productivity
If application components are distributed to edge servers, then real-time performance and scalability are improved, but system complexity and data synchronization challenges increase
Solution Approach 1:
The patent creates a standardized edge server architecture where each edge server is designed to perform multiple functions: handling local customer requests, caching data, processing transactions, and synchronizing with the central cloud. This universal design reduces system complexity by using identical multi-functional units rather than specialized components for each function.
Solution Approach 2:
The patent implements dynamic configuration parameters that allow edge servers to adapt their behavior based on local conditions and central cloud policies. By changing operational parameters rather than system architecture, the patent maintains real-time performance while managing complexity through software-based control rather than hardware complexity.
3Ease of operation
If a multidimensional value model is used to process user inputs in real-time, then personalized recommendations and user experience are improved, but processing time and computational resources increase
Solution Approach 1:
The patent pre-computes and caches value model data at edge servers before users make requests. By performing preliminary actions to prepare recommendation data in advance, the system can deliver personalized recommendations in real-time without incurring computational delays during actual user interactions, thus improving user experience while minimizing processing time.
Solution Approach 2:
The patent implements local value model processing at edge servers rather than centralized processing. Each edge server maintains and processes value models locally for its regional users, reducing the computational burden on any single server and enabling faster local processing. This local quality approach distributes computational resources and reduces processing time for personalized recommendations.
Data Source
AI summary
Provided herein is a non-transitory computer readable medium comprising software configured to enable instructions to create of a multidimensional value model for an event, such as, a travel event. When executed information related to events from all sources is stored and categorized according to the source, value dimension and value description of the event are established and used to create an initial multidimensional value model. If the event is a travel event, the initial model is updated according to user-selected travel events and a recommendation for travel made to the user based on the updated model. Also provided is a distributed cloud computer system that integrates cloud computing with a Distributed Internet Services system and cloud computing methods, particularly, for improving user experience during e-commerce transactions. A non-transitory storage medium tangibly stores processor-executable instructions to execute the methods.