Adaptive Media Buffer Sizing for Low-Latency Rewind
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Solution Overview
Problem
Media systems face inefficiencies due to fixed buffer sizes leading to latency and memory consumption issues when users rewind media assets, as they often require slow and inefficient requests to remote devices, and maintaining large buffers degrades system performance.
Innovation Solution
Adjusting buffer size based on the likelihood of a user requesting a rewind by leveraging metadata and user profiles, increasing the buffer during critical segments and reducing it when not needed, thus avoiding unnecessary requests to remote devices and optimizing memory usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If a fixed buffer size is used to store media asset portions, then the buffer structure is simple and stable, but when users rewind too far the needed portion may not be contained in the buffer requiring slow requests to remote devices
Solution Approach 1:
The buffer size is made dynamic rather than fixed. The system continuously monitors user rewind behavior and adjusts the buffer size accordingly - expanding it when rewind requests exceed the fixed size and contracting it when they don't. This dynamic adjustment ensures the buffer can accommodate user rewind needs without requiring slow remote requests while avoiding unnecessary memory consumption.
Solution Approach 2:
The buffer management system operates autonomously by monitoring its own performance metrics (rewind request patterns) and self-adjusting the buffer size without external intervention. When the system detects that rewind requests are exceeding the current buffer capacity, it automatically expands the buffer; when requests are within capacity, it contracts the buffer to free memory resources.
2Ease of operation
If a large buffer is maintained at all times to accommodate rewind requests, then rewind operations remain fast and smooth, but limited random-access memory is consumed and overall system performance degrades
Solution Approach 1:
The buffer size dynamically adapts to actual user needs rather than maintaining a constant large size. By continuously monitoring rewind request patterns and adjusting the buffer capacity accordingly, the system ensures smooth rewind operations when needed while freeing memory resources when large buffers are not required, thus resolving the contradiction between operation smoothness and memory consumption.
3Reliability
If the buffer size is increased to accommodate frequent rewind requests, then rewind operations remain smooth, but memory resources are wasted during segments where rewinds are not needed
Solution Approach 1:
The buffer size is dynamically adjusted based on real-time monitoring of user rewind behavior during different media segments. When rewind requests are frequent, the buffer expands to ensure reliable fulfillment; when requests are rare, the buffer contracts to free memory resources. This dynamic approach maintains high rewind fulfillment reliability while minimizing memory resource waste.
Solution Approach 2:
The system changes the buffer size parameter dynamically based on observed user behavior patterns. By monitoring rewind request frequency and duration during different segments of media assets, the system adjusts the buffer size parameter to match actual user needs, ensuring reliable rewind fulfillment while avoiding memory waste during segments where large buffers are unnecessary.
Data Source
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AI summary
Methods and systems are provided for adjusting a size of a buffer based on a probability that a rewind request will be received during a currently playing segment of media. When the system determines that receiving a rewind request is likely, the system will increase the size of a buffer such that the rewind request can be accommodated using data from the buffer. When the system determines that receiving a rewind request is unlikely, the system will decrease the size of the buffer to free resources for other system components.