Dynamic Endpoint Generation for Streaming Data
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Solution Overview
Problem
Conventional data streaming systems face challenges in scalability, latency, and bandwidth efficiency, particularly in edge environments, due to the reliance on centralized architectures and static endpoints, which become costly and latency-prone for high-volume media streams.
Innovation Solution
The method involves sending stream registration requests to a server, receiving stream addresses and protocol parameters for dynamic transmission endpoints, and establishing data links that adapt to changing conditions, allowing for the creation and migration of new endpoints while maintaining continuous data streaming.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a centralized architecture with static endpoints is used for data streaming, then system simplicity is maintained, but bandwidth costs and latency increase for high-volume media streams
Solution Approach 1:
The patent segments the centralized streaming architecture into multiple distributed edge endpoints. Instead of routing all data through a single centralized server, the system creates multiple edge endpoints that can locally process and stream data, reducing latency and bandwidth costs while maintaining system manageability through standardized interfaces.
Solution Approach 2:
The patent introduces a new dimensional approach by deploying endpoints across multiple geographic locations and network edges rather than concentrating all streaming operations in a single centralized location. This spatial distribution reduces latency by placing processing closer to data sources and consumers.
2Reliability
If multiple static endpoints are provisioned for failover and scalability, then system reliability is improved, but resource utilization efficiency decreases
Solution Approach 1:
The patent implements dynamic endpoint management where endpoints can be created, activated, or deactivated based on real-time streaming demands. Instead of provisioning multiple static endpoints that remain idle when not needed, the system dynamically allocates endpoint resources to match actual workload requirements, improving both reliability and resource efficiency.
Solution Approach 2:
The patent changes the operational parameters of endpoints from static to dynamic configurations. Endpoints can adjust their capacity, protocols, and active state based on streaming conditions, allowing the system to maintain reliability through multiple available endpoints while optimizing resource utilization by activating only those needed for current demand.
3Device complexity
If centralized data processing is used, then data management is simplified, but bandwidth costs and latency increase
Solution Approach 1:
The patent extracts data processing functionality from the centralized cloud environment and places it at the network edge. By taking out processing capabilities from the central data center and distributing them to edge endpoints, the system reduces bandwidth consumption for data transmission while maintaining simplified data management through standardized protocols and interfaces.
Data Source
AI summary
Methods and apparatuses are provided to improve streaming of data by providing efficient media ingress and egress. A method may include sending a plurality of stream registration requests for streams to stream data. The method may also include receiving a plurality of stream addresses. The method may further include establishing a plurality of data links with the plurality of transmission endpoints, and establishing a new data link with a new transmission endpoint according to changing conditions affecting a user equipment, while preserving the same data streams for streaming the data.