Service-Based Data Analytics Management Architecture for 5G Network Slices
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Solution Overview
Problem
Current network communication systems lack a flexible and scalable data analytics management (DAM) architecture that can efficiently analyze and optimize resource utilization across network slices and services, leading to suboptimal network performance and management challenges in 5G networks.
Innovation Solution
A service-based architecture for data analytics management (DAM) is introduced, comprising a method and apparatus that configures network devices to collect, process, and transmit network operating information, enabling resource scaling, performance assurance, and dynamic network operations through a hierarchical and domain-specific framework.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a traditional network management architecture is used, then the system structure is simple, but it cannot provide flexible and scalable data analytics management for network slices
Solution Approach 1:
The patent divides the network management system into separate network functions (NWDAF for data analytics, NFMAN for management, NFV MANO for virtualization) that can operate independently. Each function is segmented to handle specific tasks, allowing the system to scale flexibly while maintaining manageable complexity through functional decomposition.
Solution Approach 2:
The patent creates a universal management framework where the NFMAN function can manage multiple network slices and services through standardized interfaces. The system uses universal configuration instructions and processing operations that can be applied across different network domains, enabling multi-functionality without proportionally increasing complexity.
2Productivity
If network data is collected and processed to provide analytics, then resource utilization optimization is improved, but the complexity of data processing operations increases
Solution Approach 1:
The patent implements self-service through automated configuration instructions that enable network devices to collect, process, and transmit their own operating information without requiring complex manual intervention. The system automatically configures analytics functions and processes data based on predefined instructions, improving resource utilization while keeping processing complexity manageable through automation.
Solution Approach 2:
The patent uses parameter changes by configuring network devices with specific processing operations and configuration instructions that can be dynamically adjusted. The system can change processing parameters based on network conditions, allowing efficient resource utilization through adaptive processing while maintaining manageable complexity through parameterized rather than hard-coded solutions.
3Reliability
If multiple network devices are configured to collect and process information, then network performance assurance is improved, but the complexity of configuration management increases
Solution Approach 1:
The patent applies preliminary action through pre-configured processing operations and configuration instructions that are prepared in advance. The system pre-defines how network devices should collect, process, and transmit information, so that when operations are executed, they follow predetermined reliable patterns. This reduces the complexity of real-time configuration management while ensuring consistent network performance assurance.
Data Source
Figure 1A~1B
Figure 1C
Figure 2A
AI summary
Methods and apparatuses for service based architecture (SBA) for data analytics management (DAM) are disclosed. Configuration specifications are provided for configuring DAM entities for infrastructure management by infrastructure managers (InfMs), customer service managers (CSMs) for network slice subnet instance (NSSI), network slice instance (NSI) and service instance (SI) management, content and forwarding managers (CFM) for content and content cache management. Also provided methods and apparatus for data analytics service provisioning regardless of DAM architecture.