Script Runtime Estimation for Dynamic Server Queue Routing

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Solution Overview

Problem

The increasing demand for server resources due to user-generated scripts leads to performance issues, necessitating efficient management of script execution to enhance user experience and reduce server load.

Innovation Solution

A system that estimates script runtime using machine learning algorithms, categorizes scripts based on runtime, and routes them to appropriate servers for execution, utilizing image representations or salient patterns to optimize server queues.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If more user-generated scripts are executed on servers, then user engagement and customization capability improve, but server performance and system responsiveness deteriorate

Engineering Contradiction:

Improveuser customization capabilityVSAvoidserver performance

Core Design Contradiction:

Adaptability or versatilityVSProductivity

Solution Approach 1:

The patent segments scripts into different complexity categories (simple, moderate, complex) based on runtime estimates, and routes them to different server queues. This segmentation allows the system to handle diverse script requirements efficiently, preventing complex scripts from blocking simpler ones and maintaining overall server performance while supporting user customization.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system performs preliminary analysis of scripts by generating image representations and using machine learning models to estimate runtime before execution. This preliminary action categorizes scripts into complexity levels, enabling proactive resource allocation and queue management, thus preventing performance degradation before it occurs.

Inventive Principle:

Principle #10Preliminary action

2Device complexity

If scripts are executed in first-come-first-served order, then system simplicity is maintained, but wait time for complex scripts increases

Engineering Contradiction:

Improvequeue management complexityVSAvoidscript execution wait time

Core Design Contradiction:

Device complexityVSLoss of time

Solution Approach 1:

The patent implements dynamic queue management where scripts are routed to different queues based on their estimated complexity. The system dynamically adjusts execution priorities and resource allocation based on real-time script characteristics, allowing complex scripts to be handled by appropriate server resources without blocking simpler scripts, thus reducing overall wait time.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

Different server queues are optimized for different script complexity levels. Simple scripts are processed by resources optimized for speed, while complex scripts are handled by resources with higher computational capacity. This local optimization ensures that each queue operates at peak efficiency for its specific workload type.

Inventive Principle:

Principle #3Local quality

3Measurement precision

If runtime estimation accuracy is improved, then resource allocation optimizes, but processing overhead increases

Engineering Contradiction:

Improveruntime estimation accuracyVSAvoidprocessing overhead

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The system creates image representations (copies) of scripts that capture their essential characteristics without requiring full execution. These image representations are processed by machine learning models to generate runtime estimates, providing accurate predictions with minimal processing overhead compared to actual script execution.

Inventive Principle:

Principle #26Copying

Solution Approach 2:

The patent replaces traditional runtime estimation methods (which might involve partial execution or detailed code analysis) with machine learning-based prediction. The ML model learns patterns from historical data and provides accurate runtime estimates by analyzing script image representations, significantly reducing processing overhead while maintaining or improving accuracy.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS12530211B2Systems and methods for dynamic server control based on estimated script complexity

Publication Date: 2026.01.20 CHARLES SCHWAB & CO INC

AI summary

A computer system includes processor hardware and memory hardware storing instructions for execution by the processor hardware. The instructions include, in response to receiving a first script from a user device, compiling the first script, generating an image representation of the compiled first script, and determining an estimated runtime of the first script using a machine learning algorithm. The instructions include transmitting the estimated runtime for display on a display of the user device, categorizing the estimated runtime, and transmitting the first script to a queue based on the categorization. The instructions include, in response to the first script reaching a front of the queue, executing the first script on a server of the plurality of servers that corresponds to the queue. The instructions include, in response to the first script being executed, transforming the display of the user device according to instructions of the first script.