Adaptive Streaming Encoder for Time-Varying Network Connections
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Solution Overview
Problem
In data streaming systems, existing technologies fail to adaptively manage flow rates in response to time-varying connection conditions, particularly for delay-sensitive data, leading to potential service quality degradation due to fluctuations in network load and transmission media conditions.
Innovation Solution
A method and system for dynamically adjusting the encoding rate of data streams based on real-time measurements of connection performance characteristics, such as transfer delay and data loss, using encoding coefficients calculated from regression analysis and buffer occupancy metrics to ensure optimal flow rates that meet both delay and loss requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the encoding rate is increased to improve data transmission speed, then productivity is improved, but the reliability deteriorates due to buffer overflow and data loss in time-varying connections
Solution Approach 1:
The encoding rate is made dynamic rather than fixed, allowing it to adapt to time-varying connection conditions. The system continuously monitors connection state and adjusts the encoding rate accordingly, transforming a static parameter into a dynamic one that responds to changing network conditions, thus resolving the contradiction between maintaining high transmission speed and ensuring reliable delivery
Solution Approach 2:
The system implements feedback mechanisms where connection state information (such as buffer occupancy, packet loss, and delay measurements) is continuously monitored and fed back to the encoder. This feedback loop enables the encoder to adjust its encoding rate based on actual connection conditions, preventing buffer overflow while maximizing transmission efficiency under varying network states
2Reliability
If the encoding rate is decreased to improve reliability and prevent data loss, then reliability is improved, but the productivity deteriorates due to reduced data transmission speed
Solution Approach 1:
Rather than using a fixed low encoding rate, the system dynamically adjusts the encoding rate based on real-time connection conditions. When connection quality is good, the encoding rate increases to maximize throughput; when connection quality deteriorates, the rate decreases to prevent data loss, thus resolving the contradiction by making the rate adaptive rather than statically conservative
Solution Approach 2:
The system changes the encoding rate parameter in response to varying connection conditions. By monitoring connection state metrics and adjusting the encoding rate parameter dynamically, the system optimizes the balance between transmission speed and data loss prevention, avoiding the need for a permanently reduced encoding rate
3Reliability
If real-time connection state evaluation is implemented to improve service quality adaptation, then reliability is improved, but the device complexity increases due to additional measurement and control mechanisms
Solution Approach 1:
The system enables the encoder to self-adjust its encoding rate based on connection state feedback without requiring complex external control mechanisms. The encoder autonomously monitors connection conditions and modifies its own operation, reducing the need for additional complex control infrastructure while maintaining reliable service quality
Solution Approach 2:
The system design allows existing components to serve multiple functions. For example, the same communication infrastructure used for data transmission also carries feedback information about connection state. This multi-functionality reduces the need for separate dedicated measurement and control channels, thereby limiting the increase in device complexity while still achieving real-time adaptation
Data Source
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AI summary
A system and methods for adapting streaming data for transmission over a connection of time-varying capacity are disclosed. A streaming server individually adapts transmission rates of signals directed to subtending clients according to measurements characterizing connections from the streaming server to the clients. The measurements may relate to characteristics such as transfer delay, data-loss fraction, and occupancy level of a buffer at a client's receiver. A flow controller associated with the streaming server derives metrics from measurements taken over selected time windows to determine a permissible transmission rate from the server to each active client. Metrics related to a specific characteristic may include a mean value over a moving window as well as short and long term tendencies of respective measurements. An adaptable encoder at the streaming server encodes signals to meet permissible transmission rates.