Dynamic Rate Adjustment for Content Delivery QoE and Cost
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Solution Overview
Problem
Existing content delivery systems face challenges in optimizing Quality of Experience (QoE) while minimizing delivery costs, particularly in networks with unreliable Quality of Service (QoS), where data loss and packet delays can lead to distorted or interrupted video playback, resulting in user dissatisfaction and increased costs due to unnecessary data transmission.
Innovation Solution
A content delivery system that includes a server and client device capable of calculating and adjusting transmission and media rates based on an objective function evaluating both QoE and delivery cost, using variables such as packet loss, media rate, and transmission rate to optimize content delivery over networks with varying bandwidth.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a large-capacity band is secured to ensure QoS and prevent data loss, then video quality and user QoE are improved, but delivery cost increases
Solution Approach 1:
The patent implements dynamic rate adjustment where the transmission rate and media rate are continuously adapted based on real-time network conditions and user behavior. The system calculates optimal rates using an objective function that balances QoE and delivery cost, allowing the system to respond dynamically to changing bandwidth availability rather than maintaining a fixed high-capacity allocation
Solution Approach 2:
The system changes key parameters (transmission rate and media rate) based on network conditions and user behavior patterns. By adjusting these parameters dynamically, the system can maintain acceptable video quality while reducing the overall bandwidth capacity required, thereby lowering delivery costs
2Productivity
If transmission rate is increased to deliver more data quickly, then video reproduction continuity is improved, but packet loss probability increases
Solution Approach 1:
The patent employs feedback mechanisms where the system monitors network conditions and user behavior in real-time, then uses this information to adjust transmission and media rates. This closed-loop control allows the system to optimize data delivery speed while maintaining packet loss within acceptable limits by adapting to changing network conditions
Solution Approach 2:
The transmission rate is made dynamic rather than fixed, allowing the system to increase speed when network conditions are favorable and reduce speed when congestion is detected, thereby balancing productivity and reliability
3Reliability
If media rate is increased to improve content quality, then user QoE is improved, but delivery cost increases
Solution Approach 1:
The media rate is dynamically adjusted based on network conditions and user behavior patterns. The system calculates optimal media rates using an objective function that balances content quality with delivery cost, changing the parameter as needed rather than maintaining a consistently high rate
Solution Approach 2:
The system automatically adjusts media rate based on monitored user behavior (such as pause, rewind, fast-forward actions) without requiring manual intervention. When users exhibit behaviors indicating lower quality requirements, the system autonomously reduces media rate to lower delivery cost
4Loss of energy
If available network band is narrowed, then delivery cost is reduced, but video distortion and reproduction stop occur
Solution Approach 1:
The system dynamically adjusts both transmission rate and media rate in response to available network bandwidth. When bandwidth is limited, the system reduces rates to maintain playback continuity and prevent distortion, while still delivering acceptable quality content
Solution Approach 2:
The system monitors network conditions continuously and uses feedback to adjust delivery parameters. When bandwidth availability decreases, the feedback mechanism triggers rate reduction to prevent video distortion and reproduction stops, maintaining playback continuity at reduced quality
Data Source
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AI summary
The server device 100 transmits media data of a media rate, calculated by the rate output means 102, to the client device 200 at a transmission rate calculated by the rate output means 102. The rate output means 102 uses an objective function, which uses a media rate and a transmission rate as variables and determines an evaluation value evaluating a combination of QoE and a delivery cost so as to correspond to the variables, and predetermined constrains, to calculate a combination of a media rate and a transmission rate with which the evaluation value is the highest. The client device 200 reproduces content based on the media data transmitted from the server device 100.