Performance Measurement System for Web Content Delivery Optimization
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Solution Overview
Problem
Current methodologies for monitoring and optimizing data exchanges between client computing devices and server computing devices are limited in their ability to assess performance metrics across the entire data exchange process, particularly in considering latency and resource configurations, leading to suboptimal delivery of web content and resources.
Innovation Solution
A performance measurement system that includes client computing devices, content providers, and processing devices to collect and analyze performance metrics from both client and server sides, dynamically identifying resource configurations based on display locations and usage patterns to improve subsequent requests.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current methodologies for monitoring data exchanges are used, then implementation is simple, but performance assessment capability is limited
Solution Approach 1:
The system segments performance monitoring into multiple specialized components: client-side monitoring agents, server-side monitoring agents, and a central analysis server. Each component handles specific aspects of performance data collection and analysis, enabling comprehensive performance assessment while distributing system complexity across modular units rather than requiring a monolithic complex system.
Solution Approach 2:
The patent introduces performance monitoring agents as intermediary components that bridge client devices, server devices, and the analysis server. These agents collect, format, and transmit performance metrics data, serving as intermediaries that enable comprehensive performance assessment without requiring direct complex interactions between all system components.
2Measurement precision
If comprehensive performance metrics are collected across entire data exchange process, then performance assessment improves, but data processing load increases
Solution Approach 1:
The system performs preliminary actions by collecting and formatting performance metrics data at the source (client and server devices) before transmission to the analysis server. Monitoring agents pre-process data locally, filtering and organizing metrics into standardized formats, which reduces the processing load on the central analysis server and minimizes energy consumption during data transmission and centralized processing.
Solution Approach 2:
The patent implements partial action by selectively monitoring and collecting only relevant performance metrics based on predefined criteria and thresholds. The system focuses on collecting specific metrics such as latency, bandwidth utilization, and error rates that are most critical for performance assessment, rather than indiscriminately collecting all possible data, thereby reducing overall data processing load while maintaining effective performance monitoring.
3Productivity
If resource configurations are optimized based on performance data, then delivery efficiency improves, but analysis and processing requirements increase
Solution Approach 1:
The system implements feedback mechanisms where performance metrics data collected from client and server devices is analyzed to generate optimization recommendations, which are then applied to resource configurations. The system continuously monitors the effects of these optimizations and uses the feedback to further refine configurations, creating a closed-loop system that improves delivery efficiency while managing analysis complexity through iterative refinement rather than requiring all optimizations to be determined simultaneously.
Solution Approach 2:
The patent applies parameter changes by systematically adjusting resource configuration parameters such as caching strategies, content delivery locations, and resource allocation based on analyzed performance data. The system modifies specific parameters like TTL values, cache sizes, and server selection criteria to optimize delivery efficiency, transforming complex performance analysis results into targeted parameter adjustments that improve productivity without requiring complete system reconfiguration.
Data Source
AI summary
Systems and methods for monitoring the performance associated with fulfilling resource requests and determining optimizations for improving such performance are provided. A processing device obtains and processes performance metric information associated with processing a request corresponding to a set of resources. The processing device uses the processed performance metric information to determine a resource configuration to be associated with the set of resources. In some embodiments, in making such a determination, the processing device assesses performance metric information collected and associated with subsequent requests corresponding to the content associated with the set of resources and using each of a variety of alternative resource configurations. The processing device may also consider a number of factors. Aspects of systems and methods for generating recommendations to use a particular resource configuration to process a subsequent request corresponding to the content associated with the set of resources are also provided.