Streaming Media Manifest Generation for Adaptive Bit Rate Control
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Solution Overview
Problem
Existing media distribution services face challenges in adapting to changing network conditions during media streaming, as they cannot control which fragments clients request, leading to potential disruptions in playback quality.
Innovation Solution
A manifest generation service estimates available bandwidth and latency to determine the optimal fragment for a client to request, generating manifests that direct the client to a single suitable source, ensuring seamless playback by limiting bit rate choices and managing buffer state data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the media distribution service provides multiple source options in manifests, then the client has more bit rate choices and adaptability, but the service cannot control which fragments the client requests, leading to playback disruptions
Solution Approach 1:
The manifest generation service acts as an intermediary between the media sources and the client. Instead of providing the client with direct access to multiple sources, the service generates manifests that recommend specific sources based on network conditions. This intermediary role allows the service to guide fragment selection while still providing adaptability through dynamic manifest updates.
Solution Approach 2:
The service dynamically changes the parameters in the manifest (specifically the recommended source identifiers) based on real-time network conditions such as bandwidth and latency. By adjusting these parameters in response to changing conditions, the service maintains both adaptability and control over fragment selection to ensure reliable playback.
2Ease of operation
If the client autonomously selects fragments based on network conditions, then the client has flexibility, but the media distribution service cannot control which fragments are requested, causing potential quality issues
Solution Approach 1:
The system implements feedback loops where the client reports network conditions (bandwidth, latency) back to the manifest generation service. The service uses this feedback to generate updated manifests with optimized source recommendations. This feedback mechanism allows the client to operate autonomously while the service maintains control over fragment selection quality through informed recommendations.
Solution Approach 2:
The manifest generation service performs preliminary actions by pre-calculating and recommending optimal sources in the manifest before the client makes its final selection. This preliminary guidance ensures that the client's autonomous selection is based on pre-analyzed network conditions, maintaining both client flexibility and service-controlled quality.
3Stability of the object's composition
If the service generates dynamic manifests with single source recommendations, then playback smoothness is improved, but the client has fewer bit rate choices
Solution Approach 1:
The manifest generation service dynamically updates the manifest recommendations based on real-time network conditions. While each manifest recommends a single source for stability, the service can generate new manifests with different recommendations as conditions change. This dynamic approach maintains playback smoothness through controlled fragment selection while preserving adaptability through time-varying recommendations.
Data Source
AI summary
Disclosed are various embodiments for a client application for streaming media. The client application estimates the bandwidth of the client and the latency between the client and a media distribution service. A bit rate for a media stream is determined using the latency, a buffer state, and the estimated bandwidth. A time to send the request is determined using the estimated bandwidth and latency.