Nonlinear Dynamic Prioritized Content Caching
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Solution Overview
Problem
Existing media streaming technologies face challenges in reducing playback latency and improving consumer experience due to inefficient caching of media content fragments, particularly when users skip ahead or engage with non-linear content playback.
Innovation Solution
A nonlinear, dynamic, and prioritized content caching scheme that optimizes the caching of media content fragments based on the user's current playback position, preferences, and interactions, ensuring that the most likely next fragments are cached and available for immediate playback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If linear caching of media fragments is used, then memory allocation is simplified, but playback latency increases when users skip ahead
Solution Approach 1:
The patent implements dynamic caching by continuously monitoring playback position and adjusting fragment priority in real-time. The system transitions from static linear caching to dynamic prioritization based on actual user behavior, allowing the cache to adapt and reduce latency when skip operations occur.
Solution Approach 2:
The system changes the parameter of fragment prioritization from fixed linear order to dynamic priority values. By calculating priority based on playback position and predicting future positions, the system transforms the caching strategy from a static sequence to a dynamically adjusted priority system that responds to user interactions.
2Loss of time
If more media fragments are cached in advance, then playback latency is reduced, but bandwidth usage increases
Solution Approach 1:
The system applies partial action by caching only the necessary portion of fragments based on predicted playback needs. Instead of caching excessive content, it calculates a reasonable lookahead distance and prioritizes fragments within that range, achieving latency reduction without proportionally increasing bandwidth consumption.
Solution Approach 2:
The system uses feedback from actual playback behavior to adjust caching decisions. By monitoring skip patterns and playback position changes, the system learns user preferences and optimizes which fragments to cache, reducing wasted bandwidth on fragments that are never or rarely accessed.
3Loss of time
If nonlinear prioritized caching is implemented, then playback latency for skipped content is reduced, but device complexity increases
Solution Approach 1:
The patent segments the caching management into distinct functional components: playback position monitoring, fragment priority calculation, and selective caching. This segmentation allows each component to handle a specific aspect of the complexity, making the overall nonlinear prioritized system more manageable and implementable.
Data Source
AI summary
Systems, methods, and computer-readable media are disclosed for providing a nonlinear, dynamic, and prioritized content caching scheme for segmented content during playback. Certain embodiments provide new techniques for optimally determining preferred content, prioritizing the preferred content for download and consumption, and, in systems where storage and memory systems are constrained, utilizing the same prioritization system for optimized garbage collection. Example methods may include determining a current playhead position associated with a video playback. Certain methods include determining a cache priorities for fragments based on the current playhead position and the positions of the fragments in the video playback. A first fragment may be the next fragment with respect to the linear playback, and a second fragment may follow the first fragment. Certain methods include determining that the second cache priority is higher than the first cache priority and providing the second fragment to a user device.