Video Streaming Parameter Optimization via Dynamic Service Selection
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Solution Overview
Problem
Existing video streaming systems fail to optimize parameters such as frame rate, resolution, and delay based on specific user requirements and resource limitations at both the sender and receiver ends, leading to suboptimal quality of service.
Innovation Solution
A data streaming system with a level of service selector that monitors network, streaming source, and client resources to dynamically adjust streaming parameters, such as frame rate, resolution, and delay, based on viewer preferences and available resources, including processing capacity and network bandwidth.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If load balancing systems focus on network capacity and connection conditions, then network service continuity is improved, but user-specific service requirements and quality of service are not optimized
Solution Approach 1:
The system dynamically adjusts streaming parameters (resolution, frame rate, compression) in real-time based on changing network conditions and user requirements. The load balancer continuously monitors network status and user preferences, then adapts the video stream parameters accordingly, transforming a static service into a dynamic one that responds to both network capacity and user-specific needs.
Solution Approach 2:
The invention changes multiple streaming parameters simultaneously (resolution, frame rate, compression level, delay) based on the optimization algorithm's output. By adjusting these parameters dynamically, the system can meet different user quality requirements while maintaining network efficiency, resolving the contradiction between network continuity and user-specific optimization.
2Ease of operation
If video streaming parameters are increased to improve quality, then user experience is improved, but network bandwidth and processing resources are consumed excessively
Solution Approach 1:
The system optimizes the balance between quality and resource consumption by dynamically adjusting streaming parameters. The optimization algorithm determines the maximum quality level that can be delivered within available network and processing resources, preventing both over-quality (wasting resources) and under-quality (poor user experience).
Solution Approach 2:
The system provides more than minimum required quality when resources are abundant, but scales back to exactly what is needed when resources are constrained. This partial action approach ensures user experience is maximized within resource limits rather than consistently providing excessive quality that would waste network and processing resources.
3Manufacturing precision
If multiple high resolution streams are transmitted simultaneously, then service quality is improved, but CPU processing capacity at the receiver is exceeded
Solution Approach 1:
The system adjusts resolution and frame rate parameters based on the receiver's CPU processing capacity. When processing capacity is limited, the system automatically selects lower resolution streams or reduces frame rates, preventing the receiver from being overwhelmed while still providing acceptable video quality for the given hardware capabilities.
Solution Approach 2:
The system creates multiple video streams at different quality levels (resolutions and frame rates) from the same source, allowing the receiver to select or receive only the appropriate copy based on its processing capacity. This avoids the need to transmit and process all high-resolution streams simultaneously.
4Reliability
If real-time feedback is provided for live streams, then service responsiveness is improved, but delay tolerance is reduced
Solution Approach 1:
The system dynamically adjusts streaming parameters based on real-time feedback about user requirements and network conditions. For live streams requiring immediate feedback, the system prioritizes low delay by adjusting frame rates and buffering parameters, while still maintaining acceptable quality through dynamic adaptation rather than fixed high-quality transmission.
Data Source
AI summary
A data streaming system comprises: one or more streaming sources, one or more streaming clients, a network connecting said streaming sources and said clients, and a level of service selector able for each data stream to monitor the network, the respective streaming source and the respective streaming client to control streaming to the respective streaming client to define a level of service of the data stream. For a video stream the level of service may define the frame rate, the resolution, the overall quality or a level of masking used.