Network Data Analytics for Refined Resource Allocation
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Solution Overview
Problem
Current network slice management in 5G systems faces challenges due to coarse Service Level Agreement (SLA) templates, leading to inefficient resource deployment, resulting in suboptimal network slice performance and potential resource waste or insufficiency.
Innovation Solution
A resource management method and apparatus that utilizes a network data analytics device to collect and analyze service experience data and network performance data, determining a refined network data set to adjust network resources dynamically, ensuring better alignment with service quality requirements and optimizing resource allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If coarse SLA templates are used for network slice management, then device complexity is reduced, but network slice performance deteriorates due to improper resource deployment
Solution Approach 1:
The patent segments the network management system into multiple components: network data analytics device for data collection and analysis, network management device for policy determination, and network slice management functions. This segmentation allows coarse SLA templates to be enhanced with fine-grained resource allocation through dedicated analytics functions, resolving the contradiction between simplicity and performance.
Solution Approach 2:
The network data analytics device acts as an intermediary between the coarse SLA templates and the actual network resource allocation. It collects service experience data, analyzes network performance, and provides refined resource allocation recommendations that bridge the gap between simple templates and complex deployment requirements.
2Ease of operation
If coarse SLA templates are used for resource allocation, then ease of operation is improved, but resource allocation precision deteriorates causing waste or insufficiency
Solution Approach 1:
The patent implements a feedback mechanism where the network data analytics device continuously collects service experience data from network slices, analyzes the actual resource utilization and performance, and feeds back refined resource allocation policies to the network management device. This closed-loop feedback enables precise resource allocation while maintaining operational simplicity through automated adjustments.
Solution Approach 2:
The network data analytics device performs preliminary analysis of service experience data and network performance before final resource allocation decisions are made. By pre-processing data and identifying optimization opportunities in advance, the system achieves precise resource allocation without complicating the operational workflow.
3Measurement precision
If detailed service experience data collection is implemented, then measurement precision is improved, but loss of information increases due to data volume
Solution Approach 1:
The patent extracts only the most relevant features and metrics from the collected service experience data using the network data analytics device. Instead of processing all raw data, the system identifies and extracts key performance indicators and service quality metrics that are essential for resource allocation decisions, reducing data management overhead while maintaining measurement precision.
Data Source
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AI summary
This application provides a resource management method and apparatus, and relates to the field of communications technologies, to improve performance of a communications system. The method includes: obtaining, by a data analytics function network element, a first service experience data set of a service, where each piece of first service experience data in the first service experience data set is used to indicate service quality of all users or a plurality of users in a network, wherein the service is executed by the users, and the service is run in the network; obtaining information about a first service quality requirement of the service, where the information about the first service quality requirement indicates a requirement on the first service experience data; and determining a second network data set of the network based on the first service experience data set, a first network data set of the network, and the information about the first service quality requirement, where when the network is in a state corresponding to any piece of second network data in the second network data set, the service satisfies the first service quality requirement.