Dynamic QoS Parameter Adjustment via Multi-Element Data Correlation
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Solution Overview
Problem
In 3GPP release 15, the static set of QoS parameters cannot effectively manage the constantly changing network environments and service requirements due to variations in network data and service data over time, affecting service experience in 5G systems.
Innovation Solution
A data processing method and apparatus that obtains and correlates data from multiple network elements based on service flow identifiers, enabling the determination of dynamic QoS parameters, slice resource optimization, and abnormality detection by collecting and analyzing time-varying network, service, and terminal data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If static QoS parameters are used for service management, then device complexity is reduced and ease of operation is improved, but adaptability to changing network environments and service requirements deteriorates
Solution Approach 1:
The patent implements dynamic QoS parameter adjustment by continuously monitoring network status parameters (bandwidth, latency, packet loss) and service parameters (MOS, throughput) and automatically updating QoS parameters based on current conditions. This transforms the static QoS management into a dynamic system that adapts to changing network environments and service requirements in real-time.
Solution Approach 2:
The patent establishes a feedback mechanism where service experience parameters (MOS, throughput) and network status parameters are continuously measured and fed back to the QoS management system. This feedback loop enables the system to detect changes in service experience and network conditions, and automatically adjust QoS parameters to maintain optimal service quality.
2Adaptability or versatility
If single set of QoS parameters is generated for a service, then device complexity is reduced and ease of manufacture is improved, but adaptability to time-varying service requirements deteriorates
Solution Approach 1:
The patent segments the QoS parameter management into multiple independent components: network status monitoring module, service parameter monitoring module, data correlation module, and QoS parameter generation module. Each module performs a specific function and can be independently configured and maintained, reducing the overall system complexity while enabling dynamic QoS adjustment.
Solution Approach 2:
The patent introduces a data correlation function as an intermediary between raw data collection and QoS parameter generation. This intermediary processes and correlates network status parameters with service parameters, identifying causal relationships and transforming raw data into meaningful insights that drive QoS parameter adjustment without requiring direct complex interactions between all system components.
3Measurement precision
If comprehensive network and service data are collected from multiple network elements, then measurement precision and reliability of service experience assessment are improved, but device complexity and loss of time increase
Solution Approach 1:
The patent implements preliminary action by pre-configuring data collection templates and correlation rules at each network element. Network status parameters and service parameters are pre-defined with their measurement methods and correlation relationships established in advance. This allows for rapid data collection and processing when service experience assessment is needed, reducing the time loss associated with ad-hoc data gathering.
Data Source
AI summary
A method in the embodiments of the application includes: obtaining, by a first network element, first data that corresponds to a service flow and that is on each of at least two network elements, where the first data that corresponds to the service flow and that is on each of the network elements includes a first identifier; obtaining, by the first network element based on the first identifier and the first data that corresponds to the service flow and that is on each of the network elements, second data that corresponds to the service flow, where the second data includes at least the first data that corresponds to the service flow and that is on each of the network elements.