Adaptive Compression Server for Network-Constrained Downloads
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Solution Overview
Problem
Existing multimedia resource distribution mechanisms fail to adapt to varying network conditions of users, resulting in either suboptimal quality for high-quality networks or interrupted downloads for low-quality networks.
Innovation Solution
A method where a server assesses the network quality of a client device and determines an appropriate compression level for multimedia resources, allowing for local storage and delivery of pre-compressed segments, with additional segments requested from other servers if needed, to ensure smooth and quality-adjusted downloads based on network capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If multimedia resources are compressed to achieve faster downloading, then download speed is improved, but resource quality deteriorates
Solution Approach 1:
The system dynamically adjusts the compression level of multimedia resources based on real-time network quality assessment. Different compression levels are prepared in advance, and the server selects the appropriate compression level according to the user's network conditions, making the system adaptive rather than static. This resolves the contradiction by allowing the same resource to be delivered at different quality-compression trade-offs depending on network conditions.
Solution Approach 2:
The system changes the compression parameter (compression level) of the multimedia resource based on network quality. By preparing multiple versions with different compression levels and selecting the appropriate one based on assessed network conditions, the system optimizes both download speed and resource quality dynamically, rather than using a fixed compression level for all users.
2Device complexity
If a single compression level is used for all users, then system complexity is reduced, but adaptability to different network conditions deteriorates
Solution Approach 1:
The system performs preliminary action by pre-compressing multimedia resources at multiple compression levels before distribution. This preparation work is done in advance, so when a user requests a resource, the server can quickly assess network quality and deliver the appropriate version without real-time compression, reducing system complexity while maintaining high adaptability.
Solution Approach 2:
The system applies local quality by delivering different compression levels to different users based on their specific network conditions. Each user receives a version optimized for their local network environment, rather than a uniform compression level. This is achieved by assessing individual user network quality and selecting the appropriate pre-compressed version.
3Speed
If high compression level is applied to all resources, then download speed for low-quality networks is improved, but quality for high-quality networks deteriorates
Solution Approach 1:
The system dynamically selects compression levels based on real-time network quality assessment for each user. Users with low-quality networks receive highly compressed versions for fast download, while users with high-quality networks receive less compressed versions for better quality. This dynamic adaptation resolves the contradiction by tailoring the compression level to each user's network conditions.
Solution Approach 2:
The system changes the compression parameter based on network quality assessment. By preparing multiple versions with different compression levels and selecting the appropriate one based on assessed network conditions, the system optimizes both download speed and resource quality dynamically, rather than using a fixed compression level for all users.
Data Source
AI summary
Method and device of increasing downloading speed in a network are disclosed. The method includes: a server receiving a download request from a first client device, the download request identifying a first compressible resource; obtaining a network quality assessment score of the first client device, the network quality assessment score indicating a projected download speed of the first client device; in accordance with the network quality assessment score, determining a first compression level of the first compressible resource for the first client device; searching for the first compressible resource at the determined first compression level locally at the first server; and sending a request for at least one of the one or more second segments that are not pre-stored locally at the first server to a second server of the network.