Fractional Content Pre-delivery for Uninterrupted Playback
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Solution Overview
Problem
The delivery of content to user devices from remote content sources is often slow and inefficient due to limitations in content sources, delivery networks, and user devices, leading to suboptimal user experiences during content consumption.
Innovation Solution
Systems and methods for delivering fractions of content to user devices before they are requested for playback, determining an optimal fraction based on predicted playback conditions and network capabilities using a cumulative-distribution function curve to ensure uninterrupted playback, and pre-delivering this content to local device storage for immediate access.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If content is pre-delivered to user devices before requested for playback, then playback reliability and user experience are improved, but network bandwidth consumption and device storage requirements increase
Solution Approach 1:
The system performs preliminary actions by delivering content to user devices before the actual playback request. The fractional pre-delivery system proactively transfers portions of content to local storage in advance, ensuring that when playback is requested, the content is already available locally, thereby eliminating buffering delays and improving playback reliability without requiring large amounts of content to be delivered at once.
Solution Approach 2:
The system segments content into fractions or portions that can be delivered selectively. Instead of delivering entire content files, the system divides content into manageable fractions based on predicted playback conditions, network availability, and device storage capacity. This segmentation allows reliable playback to be achieved by delivering only the necessary portions of content.
2Reliability
If larger fractions of content are pre-delivered to ensure uninterrupted playback, then playback continuity is improved, but the risk of wasted bandwidth and storage increases
Solution Approach 1:
The system dynamically changes parameters such as the fraction of content to deliver, delivery timing, and selection criteria based on real-time conditions including network bandwidth availability, device storage capacity, predicted playback duration, and historical playback patterns. This adaptive parameter adjustment ensures optimal content delivery that maximizes playback continuity while minimizing wasted bandwidth and storage resources.
Solution Approach 2:
The system incorporates feedback mechanisms that monitor actual playback performance, network conditions, and device usage patterns. This feedback is used to refine future pre-delivery decisions, adjusting the fraction and timing of content delivery based on what has worked well in the past, thereby improving playback continuity while optimizing bandwidth efficiency over time.
3Speed
If content delivery is optimized for speed, then user experience is improved, but the complexity of delivery network management increases
Solution Approach 1:
The system implements self-service mechanisms where user devices autonomously determine which content fractions to request and how to manage their local caching based on their own playback needs and network conditions. This reduces the complexity of centralized network management while maintaining fast and optimized content delivery, as each device manages its own content acquisition and playback requirements independently.
Data Source
AI summary
Systems and methods for delivering fractions of content to user devices before the content is selected or requested (e.g., a pre-delivery of content) are described. In some embodiments, the systems and methods receive an indication that content is available for pre-delivery from a content server to a user device over a network, determine a fraction (e.g., size) of the content available for pre-delivery that satisfies one or more predicted content playback conditions, and causes the determined fraction of the content available for pre-delivery to be delivered to the user device.