Network Slice Resource Scheduling via Spatial-Temporal Analysis
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Solution Overview
Problem
Current network slice management in 5G networks faces inefficiencies due to coarse Service Level Agreement (SLA) templates, leading to poor resource allocation and performance, with potential for resource waste or insufficiency.
Innovation Solution
A resource scheduling method where a slice management network element requests and receives detailed service experience information from a data analysis network element, allowing for precise area and time-based resource scheduling to improve allocation accuracy and utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If coarse SLA templates are used for network slice management, then network operation is simplified, but resource allocation accuracy deteriorates
Solution Approach 1:
The patent segments the coarse SLA templates into finer-grained template sets, each corresponding to specific service types or network slices. This segmentation allows for more precise resource allocation while maintaining operational simplicity through structured classification.
Solution Approach 2:
The patent applies local quality by assigning different SLA template granularities to different network slices or service types. Critical slices receive finer-grained templates for precise resource allocation, while less critical slices use coarser templates, optimizing both accuracy and operational simplicity locally.
2Device complexity
If rough resource deployment status is determined based on coarse SLA templates, then network management complexity is reduced, but resource utilization efficiency deteriorates
Solution Approach 1:
The patent introduces dynamic resource deployment status determination that adapts to real-time network conditions. The system continuously updates resource allocation based on actual service requirements and network state, improving utilization efficiency without permanently increasing management complexity.
Solution Approach 2:
The patent implements feedback mechanisms where resource deployment status is continuously monitored and adjusted based on actual service performance and resource consumption patterns, enabling efficient resource utilization through iterative optimization.
3Measurement precision
If detailed service experience information is collected and processed, then resource scheduling accuracy is improved, but system complexity increases
Solution Approach 1:
The patent designs a universal data analysis network element that handles multiple types of service experience information collection, processing, and analysis functions. This multi-functional approach improves scheduling accuracy while containing system complexity through consolidation rather than proliferation of separate components.
Data Source
AI summary
A resource scheduling method for a network slice is provided, where a slice management network element sends a request to a data analysis network element. The request includes service experience requirement information of a first network slice. The slice management network element receives a response sent by the data analysis network element. The response includes information about a first area and/or information about a first time that are/is of the first network slice and that correspond/corresponds to the service experience requirement information. The slice management network element sends information about a second area and/or information about a second time to a network device based on the information about the first area and/or the information about the first time. The network device schedules a resource for the first network slice based on the information about the second area and/or the information about the second time.