Proactive CDN Selection via QoS and Geospatial Analysis
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Solution Overview
Problem
Content distribution networks (CDNs) face performance degradation and quality of service issues due to high concurrent user requests, leading to delayed video starts, buffering, and inefficiencies, which can result in user dissatisfaction and monetary losses for content distributors.
Innovation Solution
A method and system for proactively selecting a CDN based on quality of service (QoS) parameters, streaming profiles, and geospatial parameters, using historic consumption patterns and dynamic monitoring to optimize content delivery, ensuring high QoS and efficient resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If CDN caches are replicated to handle increased user requests, then content delivery capacity is improved, but network performance and QoS parameters deteriorate due to delayed video starts, buffering, and increased latency
Solution Approach 1:
The patent implements dynamic CDN selection that adapts to changing network conditions, user locations, and content types in real-time. The system continuously monitors QoS parameters and automatically switches between CDNs based on current performance metrics, transforming the static cache replication approach into a dynamic, responsive system that maintains optimal performance under varying load conditions
Solution Approach 2:
The system changes multiple parameters simultaneously including CDN selection based on geographic location, content type, user device characteristics, and real-time QoS metrics. By adjusting these parameters dynamically, the system optimizes the balance between delivery capacity and service quality, selecting different CDNs for different content and user scenarios rather than uniformly replicating caches across all locations
2Ease of operation
If content is pushed to the last mile using traditional methods, then content availability is improved, but network efficiency deteriorates due to non-stochastic delivery and limited network resources
Solution Approach 1:
The system performs preliminary actions by proactively pre-positioning content in CDN caches based on predicted future demand patterns, historical consumption data, and upcoming events. This advance preparation ensures content availability when needed while optimizing network resource usage by delivering content before peak demand occurs, rather than reacting to last-mile requests in real-time
Solution Approach 2:
The system implements continuous feedback loops that monitor content consumption patterns, user behavior, and network performance metrics. This feedback informs dynamic adjustments to content push strategies, allowing the system to optimize the timing, location, and volume of content delivery to match actual demand, thereby improving both availability and network efficiency
Data Source
AI summary
A technique is provided for proactively selecting a content distribution network (CDN) for delivering content. The technique includes determining one or more CDNs from a plurality of CDNs based on at least a plurality of quality of service (QoS) parameters of each of the plurality of CDNs. The streaming profiles of content streamed by the one or more CDNs is dynamically monitored based on at least a plurality of content streaming parameters. A plurality of geospatial parameters associated with the content to be delivered to a CDN selected from the determined one or more CDNs. Further, a CDN to which the content is to be delivered is selected, from the one or more CDNs. The selection is based on at least an analysis of the historic pattern of consumption of the content, the monitoring of the streaming profiles, and the retrieved plurality of geospatial parameters.