Travel Query Caching System for Latency Reduction
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Solution Overview
Problem
Conventional travel planning systems face high computational costs and latency when processing low-fare search queries, making it economically impractical to provide real-time responses without remuneration and limiting their usage.
Innovation Solution
A caching system that pre-emptively poses travel queries to a travel planning system, stores cached travel options, and presents them to users, reducing the need for real-time calculations by using a cache database to store and retrieve travel information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional travel planning systems process low-fare search queries in real-time, then accurate travel information is provided, but high computational costs and latency occur
Solution Approach 1:
The system pre-computes and caches travel options for multiple origin-destination-date combinations before users actually query. By performing the computationally intensive travel planning calculations in advance and storing results in a cache database, the system eliminates real-time computation delays while maintaining accurate travel information availability.
Solution Approach 2:
The system creates cached copies of travel planning results from previous computations and stores them for rapid retrieval. Instead of重新计算 (re-calculating) travel options for each user query, the system retrieves pre-computed cached copies, significantly reducing response time while providing accurate travel information.
2Adaptability or versatility
If conventional travel planning systems respond to every query, then complete service coverage is provided, but high computational costs make it economically impractical without remuneration
Solution Approach 1:
The system proactively generates and caches travel options for anticipated queries before users actually submit them. By pre-computing travel information for various origin-destination-date combinations and storing in cache, the system reduces the need for expensive real-time computations while maintaining service coverage for user queries.
Solution Approach 2:
The system uses identification information (such as cookies or device identifiers) to recognize returning users and automatically retrieves their previously cached travel options without requiring them to re-submit queries. This self-service approach eliminates redundant computational costs while maintaining complete service coverage for recognized users.
3Speed
If the system caches travel options for anticipated queries, then response speed is improved, but system complexity increases
Solution Approach 1:
The caching system automatically manages itself by using user identification information to recognize returning users and retrieve their cached travel options without manual intervention. This self-service mechanism simplifies the overall system architecture by eliminating the need for complex manual cache management interfaces while maintaining fast response speeds.
Data Source
AI summary
Systems and techniques for presenting travel information to a user are described. A code that includes predetermined travel parameters specified by the user is included in a web page. Access to the web page by a user is detected. A travel query is populated with the predetermined travel parameters and a variable parameter based on identification information associated with the user. Cached travel options that are obtained from prior queries and that satisfy the travel query are presented to the user.