Adaptive Streaming Server Volatile Memory Segmentation
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Solution Overview
Problem
Traditional adaptive streaming servers face limitations in flexibility during segment file division and require redundant copies of content streams, leading to difficulties in extracting subsets and managing storage efficiently.
Innovation Solution
A streaming server system that segments content into data structures stored in random access memory, allowing for deferred segmentation and dynamic fragment retrieval based on time codes, eliminating the need for pre-segmented files on disk.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If content streams are segmented into files stored on disk for adaptive streaming, then the system can provide structured content delivery, but the system loses flexibility in extracting subsets and requires redundant storage copies
Solution Approach 1:
The patent segments the content stream into multiple fragments stored in volatile memory, each fragment corresponding to a specific time range. This segmentation enables flexible extraction of subsets without requiring redundant storage copies, as each fragment can be independently accessed and recombined based on client needs.
Solution Approach 2:
The system dynamically manages content segmentation and delivery by maintaining fragments in volatile memory and using a manifest to reference them. This dynamic approach allows the system to adapt segment boundaries and content delivery in real-time without the rigidity of pre-segmented disk files, thereby improving flexibility while reducing storage requirements.
2Ease of manufacture
If content is pre-segmented into files on disk, then storage management becomes simpler, but the system cannot efficiently perform on-demand segmentation or insert advertisements
Solution Approach 1:
The system performs preliminary segmentation of content into fragments and stores them in volatile memory before delivery. This preliminary action enables efficient on-demand retrieval and manipulation of content subsets, as the fragments are already prepared and accessible in memory, eliminating the need for complex disk-based segmentation operations during runtime.
Solution Approach 2:
The patent introduces a manifest as an intermediary data structure that references the segmented content fragments. The manifest enables simple storage management by providing a centralized index, while simultaneously enabling complex on-demand operations by allowing dynamic selection and recombination of fragments based on client requests, advertisements, or other criteria.
3Productivity
If multiple redundant copies of content streams are stored, then the system can serve multiple clients simultaneously, but storage efficiency decreases
Solution Approach 1:
Instead of storing multiple redundant physical copies of content streams on disk, the patent creates virtual copies by referencing the same set of segmented fragments in volatile memory through different manifest configurations. This copying approach enables multiple clients to be served simultaneously from the same physical storage resources, dramatically improving storage efficiency while maintaining concurrent service capability.
Data Source
AI summary
An adaptive streaming server, a method, and a system are described herein that create a content stream to be delivered to one or more clients by segmenting the content into data structures which are stored in random access memory (volatile storage) rather than segmenting the content into segment files which are stored on a disk or database (non-volatile storage).