Dynamic CDN Selection via User Fingerprinting and Performance Metrics
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Solution Overview
Problem
Existing systems for selecting a content delivery network (CDN) in internet communications lack efficiency in dynamically assigning users to the best-performing CDN, leading to potential video content quality issues.
Innovation Solution
A method that involves generating user or device fingerprints based on various characteristics, associating these with user populations, and dynamically reassessing and reassigning CDNs based on performance metrics to ensure optimal video content delivery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a static CDN assignment method is used, then system complexity is reduced, but video content delivery quality deteriorates
Solution Approach 1:
The patent implements dynamic CDN selection by continuously monitoring performance metrics (latency, throughput, error rates) and automatically reassigning users to optimal CDNs based on real-time conditions. This transforms the static CDN assignment into a dynamic system that adapts to changing network conditions, thereby improving video content delivery quality without requiring overly complex manual intervention systems.
Solution Approach 2:
The system establishes a feedback loop by continuously collecting performance data from CDN operations, analyzing metrics such as latency and throughput, and using this information to make informed CDN selection decisions. This feedback mechanism enables the system to learn from past performance and optimize future CDN assignments, improving delivery quality while maintaining manageable system complexity through automated decision-making.
2Reliability
If dynamic CDN reassignment is implemented, then video content delivery quality is improved, but system complexity increases
Solution Approach 1:
The patent enables the CDN selection system to operate autonomously by implementing automated performance monitoring, metric analysis, and reassignment decision-making. The system self-manages the complexity of dynamic CDN selection by automatically collecting data, evaluating performance, and executing reassignments without requiring proportionally complex external control systems, thereby improving delivery quality while keeping system complexity manageable.
Solution Approach 2:
The system manages complexity by focusing on key performance parameters (latency, throughput, error rates) rather than attempting to optimize all possible CDN attributes simultaneously. By monitoring and responding to changes in these critical parameters, the system achieves effective dynamic CDN selection without requiring overly complex analysis of every possible system variable.
3Measurement precision
If user fingerprints are generated and analyzed, then CDN selection precision is improved, but information processing requirements increase
Solution Approach 1:
The patent extracts only the essential characteristics needed for CDN selection by generating user fingerprints that capture key identifying features (device type, location, usage patterns) without processing unnecessary user data. This selective extraction approach improves CDN selection precision by focusing on relevant user attributes while minimizing computational resource consumption by avoiding analysis of extraneous information.
Data Source
AI summary
A method includes, at a first time: receiving a request for video content from a first user; generating a fingerprint for the first user; associating the first user with a first user population—assigned to a first CDN and receiving the video content from the first CDN during the first time period—based on the fingerprint; and accessing a first metric for distribution of video content from the first CDN to users of the first user population. The method also includes, at a second time: selecting a second user within the first user population; identifying a second CDN distinct from the first CDN; reassigning the second user to the second CDN; and accessing a second metric for distribution of the video content from the second CDN to the second user; and, in response to the second metric exceeding the first metric, reassigning the first user to the second CDN.