Surrogate Server Content Distribution via Semantic Affinity

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Solution Overview

Problem

Existing Content Delivery Networks face challenges in reducing response time to user requests and optimizing content availability at geographic locations, particularly for large and high-bitrate content, without resorting to complex architectures.

Innovation Solution

A method and system for controlling media content distribution over a network using surrogate servers, which involves identifying eligible contents, defining categories, associating contents based on semantic affinity, and generating control signals to make additional contents available at optimized locations based on usage data and interest thresholds.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If content is distributed using traditional CDN surrogate servers, then content availability is improved, but response time to user requests increases due to lack of predictive pre-positioning

Engineering Contradiction:

Improvecontent availabilityVSAvoidresponse time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system performs preliminary actions by analyzing usage data and forecasting future content requests before they occur. Surrogate servers pre-position content at optimized geographic locations based on predicted demand patterns, so that when users actually request content, it is already available locally, reducing response time while maintaining availability

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system continuously collects usage data from surrogate servers and feeds it back into the forecasting mechanism. This feedback loop enables the system to learn from actual user behavior patterns and refine its predictions, dynamically adjusting content pre-positioning strategies to optimize both response time and content availability

Inventive Principle:

Principle #23Feedback

2Measurement precision

If manual content distribution management is used, then control precision is improved, but system complexity increases due to manual intervention requirements

Engineering Contradiction:

Improvecontrol precisionVSAvoidsystem complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The system enables self-service by automating the content distribution management process. The forecasting mechanism automatically analyzes usage data, predicts content requests, and directs surrogate servers to pre-position content without manual intervention. This maintains precise control through algorithmic decision-making while reducing system complexity by eliminating manual management overhead

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system replaces manual mechanical management processes with automated computational mechanisms. Instead of human operators manually managing content distribution, the system uses forecasting algorithms and data analysis mechanisms to automatically control content pre-positioning, maintaining precision through computational accuracy while reducing operational complexity

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Reliability

If surrogate servers cache all requested content, then content availability is improved, but network bandwidth consumption increases due to redundant content transmission

Engineering Contradiction:

Improvecontent availabilityVSAvoidnetwork bandwidth consumption

Core Design Contradiction:

ReliabilityVSLoss of energy

Solution Approach 1:

The system applies local quality by having each surrogate server cache only the specific content that is predicted to be requested in its local geographic area. Instead of uniformly caching all content across all servers, the forecasting mechanism determines which content should be pre-positioned at which locations based on local usage patterns, improving availability where needed while minimizing redundant bandwidth consumption

Inventive Principle:

Principle #3Local quality

4Loss of time

If content pre-positioning is performed without forecasting, then response time is improved, but resource utilization deteriorates due to lack of demand prediction

Engineering Contradiction:

Improveresponse timeVSAvoidresource utilization

Core Design Contradiction:

Loss of timeVSProductivity

Solution Approach 1:

The system performs preliminary content pre-positioning actions based on forecasted demand rather than random or uniform distribution. By using usage data analysis to predict which content will be requested, the system pre-positions only the necessary content at appropriate locations, achieving fast response times for predicted requests while avoiding waste of storage and bandwidth resources on unlikely-to-be-requested content

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS8468229B2Method and system for controlling content distribution, related network and computer program product therefor

Publication Date: 2013.06.18 TELECOM ITALIA SPA

AI summary

A method for controlling distribution of media contents over a network is provided, wherein the contents are distributed contents available at surrogate servers and remaining contents that are not available at the surrogate servers. The method includes identifying contents eligible for distribution from the remaining contents; defining a set of categories; identifying for each category at least a reference content; associating the identified contents with the predefined categories based on semantics affinity with the reference content, the semantics affinity being calculated as the distance of each of the identified contents to the at least a reference content; selecting at least one of the predefined categories; and making at least one of the identified contents associated with the selected predefined category available for distribution at the surrogate servers.