Multicast Routing Table Viewership Analysis
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Solution Overview
Problem
Conventional data collection systems for determining television viewership are slow to update, processor intensive, bandwidth intensive, and not scalable as the number of viewers increases, making it difficult for providers to gather timely and accurate viewership information.
Innovation Solution
A system and method that utilize multicast routing table data from edge routers in a media content delivery service to determine viewership information, processing this data to generate aggregated and historical viewership statistics, and sending this information to requesting devices via a network, while also providing a graphical user interface for user interaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional data collection systems are used to determine viewership information, then comprehensive viewing data can be gathered, but the system becomes slow to update, processor intensive, and bandwidth intensive
Solution Approach 1:
The patent extracts only the essential viewership data directly from multicast routing tables at edge routers, rather than collecting comprehensive data from multiple sources. This extraction approach retrieves pre-existing routing information that already contains the necessary viewership metrics, eliminating the need for complex data aggregation while maintaining accuracy and enabling real-time updates
Solution Approach 2:
The patent introduces multicast routing tables as an intermediary data source that naturally captures viewership information through the network's existing routing infrastructure. These tables serve as a mediator between content delivery and measurement systems, providing accurate viewership data without requiring additional processing or bandwidth consumption
2Measurement precision
If conventional data collection systems are used to determine viewership information, then comprehensive viewing data can be gathered, but the system becomes processor intensive
Solution Approach 1:
The system extracts viewership information directly from multicast routing tables that already contain the necessary data in structured format. This extraction method requires minimal processing compared to conventional systems that must aggregate, filter, and analyze data from multiple sources, significantly reducing processor intensity while maintaining measurement accuracy
Solution Approach 2:
The multicast routing tables automatically maintain and update themselves as part of the content delivery process, without requiring separate measurement infrastructure. The routing tables self-generate the viewership data through their normal operation, eliminating the need for dedicated processing resources for data collection and aggregation
3Measurement precision
If conventional data collection systems are used to determine viewership information, then comprehensive viewing data can be gathered, but the system becomes bandwidth intensive
Solution Approach 1:
The system extracts viewership data from multicast routing tables that already exist in the network infrastructure, rather than transmitting additional measurement data across the network. This approach retrieves information that is already locally available at edge routers, eliminating unnecessary bandwidth consumption while preserving data accuracy
Solution Approach 2:
The system retrieves copies of routing table data that are already maintained at edge routers for content delivery purposes. These copies contain the necessary viewership information and can be accessed locally without requiring additional network transmission, reducing bandwidth usage while maintaining measurement precision
4Measurement precision
If conventional data collection systems are used to determine viewership information, then comprehensive viewing data can be gathered, but the system is not scalable as the number of viewers increases
Solution Approach 1:
The multicast routing tables serve multiple functions simultaneously: they manage content delivery routing and automatically capture viewership information. This multi-functionality allows the same infrastructure to scale with viewer numbers without requiring additional measurement systems, as the routing tables naturally adapt to handle increased traffic while continuing to provide accurate viewership data
Solution Approach 2:
The routing tables automatically adapt and scale as the network grows, maintaining their structure and functionality without requiring additional processing infrastructure. As more viewers connect and more content is delivered, the routing tables self-adjust while continuing to provide accurate viewership measurements, enabling seamless system scalability
Data Source
AI summary
Systems and methods of determining viewership information are provided. A method of determining viewership information includes determining viewership information from multicast routing table data associated with one or more edge routers of a media content delivery service. Each edge router of the one or more edge routers is adapted to transmit media content streams to multiple devices via a first network. The method also includes sending data related to the viewership information to a requesting device via a second network.