Telecommunication Network Information Transfer Optimization
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Solution Overview
Problem
Existing information transfer optimization systems in telecommunications networks struggle to directly link system parameters with perceived performance, leading to ineffective optimization and difficulty in maintaining performance as consumption and transfer methods change, resulting in unpredictable user experience.
Innovation Solution
A method and device that dynamically adapt information transfer by setting Quality of Experience (QoE) objectives, continuously determining real QoE parameters, and dynamically adjusting transfer mechanisms to optimize performance, including selective acceleration, compression, and reliability, without requiring specific parameterization based on transfer or consumption methods.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If information transfer optimization systems are parameterized according to transfer means and consumption methods, then the system can be configured for specific scenarios, but the system complexity increases and requires frequent parameter revisions when transfer means or consumption methods change
Solution Approach 1:
The optimization system automatically detects current transfer means and consumption methods, then self-configures appropriate parameters without requiring manual reparameterization. The system monitors network conditions and application performance metrics to dynamically adjust optimization settings, eliminating the need for human intervention when transfer means or consumption methods change.
Solution Approach 2:
The system transitions from static parameter configuration to dynamic parameter adjustment. Optimization parameters are continuously adapted based on real-time network conditions, transfer means characteristics, and consumption method variations. This dynamic approach allows the system to maintain optimal performance across diverse scenarios without increasing configuration complexity.
2Reliability
If optimization parameters are based on SLS parameters (jitter, delay, loss), then packet transmission performance can be controlled, but the perceived performance by end users cannot be directly optimized
Solution Approach 1:
The system introduces QoE (Quality of Experience) metrics as an intermediary layer between SLS parameters and perceived performance. By measuring and optimizing QoE-specific parameters such as application-level performance metrics and user-perceived quality indicators, the system bridges the gap between technical packet transmission parameters and actual user experience, enabling direct optimization of perceived performance while maintaining packet transmission reliability.
3Productivity
If the system continuously adapts to changes in transfer means and consumption methods, then performance can be maintained, but the frequency of parameter revisions becomes humanly impossible
Solution Approach 1:
The system implements continuous feedback loops that monitor network conditions, transfer means characteristics, and consumption method variations. Automated algorithms process this feedback data and dynamically adjust optimization parameters in real-time without human intervention. This feedback-driven automation enables the system to continuously adapt to changes at a pace that would be humanly impossible, maintaining optimal performance efficiency.
Data Source
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AI summary
The invention relates to a method of optimizing the transfer of information in a telecommunication network comprising a plurality of information producers Pi, a plurality of Cj, and information consumer means transfers the said information between the said producers and the said consumers within the framework of a plurality of applications Ak, this method comprises the following steps: a) defining a quality of experience objective QoE representing the capacity of a consumer Cj to utilize the information transferred within the framework of each application Ak implemented in the network and a level of criticality of the consumers Cj and/or of the applications Ak representing the relative importance of the said applications Ak and/or of the said consumers Cj, b) determining in a continuous manner at least one parameter representative of the real quality of experience “QoE” for at least one consumer, c) dynamically determining operational settings for the transfer of information from the producers Pi to the consumers Cj as a function of the transfer means available, d) dynamically and continually adapting the said information transfer means as a function of the settings defined in step (c).