Dedicated Network Slicing Node for 4G LTE Security and Flexibility
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Solution Overview
Problem
Current communication networks, particularly 4G LTE, lack the capability for network slicing, which is essential for providing tailored quality-of-service, security, and performance characteristics to diverse users and applications, such as drone delivery and banking services, and do not efficiently manage user device connections and security levels.
Innovation Solution
Implementing a dedicated network slicing node between the radio access network and the core network, utilizing a machine learning/AI engine to dynamically provision services and security, and creating customizable network slices based on user profiles and charging models, allowing for secure connectivity and resource allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If network slicing is implemented using virtualized network functions, then network flexibility and service customization are improved, but network security and isolation between different services deteriorate
Solution Approach 1:
The patent divides the network into multiple isolated slices, each dedicated to specific services or users. Virtualized network functions are segmented into separate virtual machines or containers that operate in isolated environments, preventing security breaches in one slice from affecting others while maintaining network flexibility through independent configuration of each slice.
Solution Approach 2:
The patent introduces a network slice manager as an intermediary component that handles service requests, resource allocation, and security policy enforcement. This mediator coordinates between the physical network infrastructure and virtualized services, ensuring proper isolation and security while enabling flexible service deployment through standardized interfaces.
2Reliability
If a dedicated network slicing node is introduced, then network security and service isolation are improved, but network complexity and infrastructure requirements worsen
Solution Approach 1:
The dedicated network slicing node is designed to perform multiple functions including service request management, resource allocation, security policy enforcement, and slice provisioning. By consolidating these functions into a single multi-functional node, the patent reduces overall network complexity compared to having separate dedicated components for each function while maintaining strong service isolation.
3Adaptability or versatility
If machine learning/AI engine is used for dynamic service provisioning, then service customization and user experience are improved, but processing time and computational requirements worsen
Solution Approach 1:
The machine learning engine pre-processes service requests by predicting resource requirements, selecting appropriate network slices, and preparing configuration parameters before actual service deployment. This preliminary action reduces real-time processing time by performing computationally intensive tasks in advance based on historical data and service patterns.
Solution Approach 2:
The AI engine implements self-service capabilities by automatically provisioning services, allocating resources, and adjusting network parameters without extensive human intervention. Once trained, the system autonomously makes provisioning decisions, reducing both processing time and operational overhead while maintaining high levels of service customization.
Data Source
AI summary
In a 4G LTE wireless carrier network, network slice instances are instantiated that are configured to provide a configured set of services that are accessible to a controlled set of user devices. A service profile for a user device is identified and analyzed. When the service profile matches a configured set of services for one of the instantiated network slice instances, the user device is enabled to access the matching instantiated network instance. The provisioning of the network slice instances is performed by a dedicated node.