Bandwidth Selection Using Historical Data for Streaming
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Solution Overview
Problem
Current streaming services often rely on a best guess approach for initial bandwidth settings, leading to inefficiencies such as blurry pictures and underutilization of bandwidth, as users and service providers take time to adjust, resulting in suboptimal user experience and resource utilization.
Innovation Solution
A system and method that determine the initial bandwidth setting by analyzing network conditions and utilizing a previously saved bandwidth setting associated with a client, stored in a memory or database, to initiate communication sessions more efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If a best guess approach is used for initial bandwidth settings, then the system can start quickly without requiring complex analysis, but it leads to blurry pictures and underutilization of bandwidth
Solution Approach 1:
The system performs preliminary action by retrieving and utilizing previously saved bandwidth settings from memory or database before initiating a new communication session. This allows the system to start with an informed guess based on historical data rather than making a random best guess, thereby improving both speed and accuracy simultaneously.
Solution Approach 2:
The system implements feedback by continuously monitoring network conditions and using this information to adjust bandwidth settings. The previously saved bandwidth settings serve as feedback from past sessions, allowing the system to learn from historical performance and make more accurate initial settings for future sessions.
2Manufacturing precision
If the system waits for clients or service providers to adjust bandwidth settings, then optimal bandwidth can be achieved, but it takes time resulting in blurry pictures and resource underutilization
Solution Approach 1:
The system performs preliminary action by pre-retrieving previously saved bandwidth settings before the communication session starts. This eliminates the need to wait for adjustment during the session, as the optimal setting is already prepared and can be applied immediately, thus reducing time loss while maintaining accuracy.
Solution Approach 2:
The system practices self-service by automatically utilizing its own historical data (previously saved bandwidth settings) to make informed initial decisions. This self-learning mechanism eliminates the need for manual adjustment or waiting for external optimization, allowing the system to achieve optimal bandwidth settings independently and immediately.
3Reliability
If flat rate data services are provided, then users have guaranteed bandwidth, but it limits user activities and inefficiently utilizes network resources
Solution Approach 1:
The system implements dynamics by transitioning from static flat-rate bandwidth allocation to dynamic bandwidth selection. The system determines optimal bandwidth settings based on actual network conditions and historical performance data, allowing bandwidth to be adjusted according to real-time demands. This maintains reliability through informed decision-making while improving productivity by allocating bandwidth efficiently rather than guaranteeing fixed amounts.
Data Source
AI summary
A system and method for selecting an initial bandwidth setting. A determination is made that a client is initiating a communication session. Network conditions for the client are determined. A bandwidth setting for the client is selected utilizing the network conditions and a previous bandwidth setting saved in a memory. The communication session for the client is initiated utilizing the bandwidth seating.