Data Distribution Platform With Client-Side Stream Filtering
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional data distribution platforms lack fine-grained access control and quality of service modulation, leading to inefficient data transmission and system dimensioning issues, as developers are not allowed to selectively access only the data feeds they are interested in, resulting in excess capacity and inability to prioritize clients.
Innovation Solution
A processing entity with a processing unit that receives data streams from generating devices and client requests, translates selection criteria into data stream modifications, filters data streams based on client specifications, and provides modified streams, allowing clients to select specific data packages with defined service level conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional data distribution platforms provide all data feeds to all clients, then clients can access any data they might need, but system capacity increases excessively and resources are wasted transmitting unnecessary data
Solution Approach 1:
The patent extracts only the necessary data from the complete data stream based on client-specific selection criteria. The processing entity filters the data stream to extract only those data points that match the client's specified criteria, thereby reducing the quantity of data transmitted while maintaining access flexibility.
Solution Approach 2:
The patent segments the data stream into individual data points and applies selection criteria to each segment. By dividing the continuous data stream into discrete filterable units, the system can selectively transmit only relevant portions to each client, optimizing resource utilization.
2Reliability
If conventional platforms transmit all data streams to all clients, then no data is lost, but transmission bandwidth and processing resources are inefficiently consumed
Solution Approach 1:
The processing entity extracts only the necessary data points from the complete data stream based on client-specific selection criteria. This extraction approach ensures that clients receive complete and reliable data matching their needs without the energy waste of transmitting unnecessary data points.
3Adaptability or versatility
If conventional platforms allow broad data access, then clients can find any data they need, but the system cannot prioritize or modulate service quality for different clients
Solution Approach 1:
The patent applies different service quality levels to different clients based on their specific needs and selection criteria. Each client receives data processing tailored to their local requirements, allowing the system to modulate service quality individually for each client while maintaining broad data access capability.
4Ease of operation
If conventional platforms provide unrestricted data access, then clients have maximum flexibility, but system dimensioning becomes excessive and costly
Solution Approach 1:
The processing entity extracts only the necessary data based on client criteria, thereby simplifying system dimensioning. By extracting only required data points rather than transmitting complete data streams, the system reduces the complexity of infrastructure requirements while maintaining client access freedom.
Data Source
AI summary
In a processing entity receiving one or more streams of data points from at least one data generating device; receiving, from a client device, a stream request indicating at least one of the data streams and including information indicating a stream modification; translating the information indicating a stream modification to selection criteria relative to the data points of the at least one data stream; modifying the at least one data stream by filtering the data stream based on the translated selection criteria; and providing the modified data stream to the client device.