Search Engine Dynamic Configuration for Resource Optimization
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Solution Overview
Problem
Search systems face increased complexity and volume in processing search requests, requiring efficient resource utilization to maintain quality of service, which cannot be solely achieved by more performant hardware.
Innovation Solution
A method that dynamically adjusts processing resources based on current configuration and quality-of-service indicators, using reinforcement learning to determine processing parameters and update configurations for future search requests, optimizing resource usage and sustainability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If more performant hardware is used to maintain quality of service, then response time is improved, but hardware cost and system complexity increase
Solution Approach 1:
The patent implements dynamic configuration adjustment where the search engine automatically modifies processing parameters (parallelization degree, resource allocation, time limits) based on real-time quality of service metrics and logged states, replacing static hardware upgrades with adaptive software control
Solution Approach 2:
The system changes operational parameters such as processing resources, parallelization degree, and time limits dynamically based on quality of service indicators and sustainability scores, allowing the same hardware to adapt its performance characteristics without physical modification
2Productivity
If processing resources are increased to handle higher search request volume, then productivity is improved, but energy consumption and environmental impact increase
Solution Approach 1:
The system implements feedback loops where quality of service indicators and sustainability scores are logged and used to automatically adjust configuration, enabling the search engine to optimize resource utilization and reduce energy consumption while maintaining processing capacity
Solution Approach 2:
The search engine autonomously adjusts its own configuration parameters based on monitored performance metrics and sustainability indicators, eliminating the need for external intervention to optimize resource usage and energy efficiency
3Productivity
If processing parameters are dynamically adjusted based on quality of service indicators, then resource utilization efficiency is improved, but system complexity increases
Solution Approach 1:
The search engine automatically monitors its own quality of service indicators and sustainability metrics, then self-adjusts configuration parameters without external control, simplifying the overall system architecture despite the complexity of dynamic optimization
Data Source
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AI summary
A search engine determines, based on a current configuration and a received search request, a number of processing parameters indicative of processing resources of the search engine to be utilized for processing the search request. The search engine determines a number of search results for the search request utilizing the processing resources of the search engine according to the number of processing parameters and returns a number of search results. The search engine determines a number of quality-of-service indicators for the returned search results and logs a state of the search engine indicating the processing resources of the search engine utilized for determining the number of search results and quality-of-service indicators. The current configuration of the search engine is updated based on the logged state of the search engine and the determined number of quality-of-service indicators to obtain an updated configuration of the search engine for processing future search requests.