Multicast Streaming Analysis for Scalable Data Distribution
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Solution Overview
Problem
The existing methods for data analysis in computer systems are inefficient and costly, especially when transferring large datasets, and they expose security risks due to the need for direct customer-server interactions and the inability to scale with multiple recipients.
Innovation Solution
Implementing a multicast streaming analysis method that uses UDP-based streams to distribute data to multiple recipients independently of the source server load, while maintaining security through IGMP snooping and packet control, allowing real-time analysis without revealing customer queries or analysis parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional data transfer methods are used to enable customers to analyze data, then data analysis capability is provided, but transfer costs become prohibitive and server load increases with each additional recipient
Solution Approach 1:
The patent segments the data distribution function from the analysis function. Multiple customers share a single multicast stream for data distribution, eliminating redundant transfers. Each customer independently performs analysis on the shared stream, so transfer costs do not increase with additional recipients while maintaining full analysis capability for each.
Solution Approach 2:
The multicast stream serves multiple functions simultaneously: it distributes data to multiple customers at once and enables independent analysis by each customer. This universal data distribution mechanism replaces multiple individual transfer operations, significantly reducing overall transfer costs while scaling efficiently to any number of recipients.
2Ease of operation
If direct customer-server interactions are implemented for data analysis, then data access is enabled, but security risks increase
Solution Approach 1:
The patent introduces a multicast stream as an intermediary between the server and customers. The server publishes data to the multicast stream without direct customer connections, and customers subscribe to the stream for analysis. This intermediary architecture enables data access while eliminating direct interaction security risks, as the server never directly communicates with individual customers.
Solution Approach 2:
The multicast stream creates a copy of the data distribution mechanism that is independent of direct server-customer connections. Multiple customers receive identical copies of the data stream simultaneously, enabling easy data access for analysis while the server maintains a single publish point without direct interaction vulnerabilities.
3Adaptability or versatility
If data is transferred to multiple customers for analysis, then analysis coverage increases, but server load increases proportionally with each recipient
Solution Approach 1:
The patent segments the data distribution task from the analysis task. The server is responsible only for publishing to the multicast stream once, while each customer independently handles their own analysis operations on the shared stream. This segmentation ensures server load remains constant regardless of the number of customers, while analysis coverage scales with each additional subscriber.
Solution Approach 2:
The multicast stream provides universal data distribution to all customers simultaneously through a single server operation. This universal mechanism allows unlimited analysis coverage across multiple customers without proportionally increasing server load, as the server performs only one publish action regardless of subscriber count.
Data Source
AI summary
A computer-implemented method for anonymously selecting streams for analysis is described. In one embodiment, control information that associates one or more telemetry feeds with one or more multicast sources is identified. One or more multicast sources are joined based on the received control information and data from the multicast source is analyzed based on one or more data analysis parameters.