Edge Server Content Distribution via AI Routing
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Solution Overview
Problem
Current Content Delivery Networks (CDNs) face challenges in efficiently distributing large multimedia content, especially during live events, due to propagation delay issues and the need for significant resource allocation to handle peak demand, leading to inefficient use of resources and potential connectivity problems across geographically dispersed POPs.
Innovation Solution
A distributed and flexible CDN architecture that eliminates the need for distributor or acquirer servers, using mathematical calculations to determine the path for content segments or fragments within the CDN, with each server maintaining minimal memory for mathematical formulas and reference addresses, allowing for efficient path determination and dynamic load distribution among intermediary servers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the CDN sizes the origin server according to possible request peaks to handle live events, then the system can cope with high demand, but the hardware resources of the origin server will be largely unused when the request peak is over
Solution Approach 1:
The patent implements dynamic resource allocation where the origin server's processing capacity is adjusted in real-time based on actual request load. During peak demand periods, the server operates at full capacity to handle live event requests, and during low-demand periods, resources are scaled down or reassigned, eliminating the waste of permanently over-provisioned hardware while maintaining the ability to cope with request peaks.
2Productivity
If distributor servers are used to cache content, then request handling during peaks is improved, but the system complexity and resource allocation become more difficult to manage
Solution Approach 1:
The patent extracts the content caching and distribution function from traditional distributor servers and implements it directly at the edge servers. This eliminates the intermediate distributor server layer, simplifying the CDN architecture while maintaining the ability to handle peak requests through intelligent caching at the network edge and direct origin-server communication when needed.
3Quantity of substance
If the origin server is located in a specific geographical area, then infrastructure costs are reduced, but connectivity problems may occur for geographically dispersed POPs
Solution Approach 1:
The patent introduces intelligent routing intermediaries that dynamically select optimal communication paths between the origin server and geographically dispersed POPs. These intermediaries monitor network conditions and route content delivery requests through the most reliable paths, ensuring stable connections even when the origin server remains in a single geographical location with reduced infrastructure requirements.
Data Source
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AI summary
An edge server (1510) of a Content Delivery Network (2000) comprises an electronic communication unit adapted to be connected to a telematic network and a processing electronic unit adapted to process data packages received and to be transmitted by the electronic communication unit; the processing electronic unit comprises a first storage sub-unit suitable adapted to store contents and a second storage sub-unit adapted to store configuration information related to a home Point Of Presence (1500) of the edge server (1510); the electronic processing unit is programmed to deal with content requests, so that in response to a request for a content if it is, in whole or in part, locally possessed, sends the content and otherwise determines a server address (1520, 1610) by performing a mathematical calculation on a name of the content taking into account configuration information, and causes a request related to the content to be sent to the server address (1520, 1610); at least the choice of server can also be influenced by artificial intelligence algorithms. Examples of embodiments of the present invention achieve high throughput and ultralow latency, i.e. they can be defined as HTULL.