Dynamic Network Slice Orchestration for 5G Service Adaptability
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Solution Overview
Problem
Current 5G networks lack the capability to dynamically create and manage network slices based on changing application requirements and network conditions, limiting their ability to provide optimized service provisioning.
Innovation Solution
The implementation of an end-to-end architecture that leverages AI engines to collect and analyze application performance requirements and network capabilities, enabling dynamic slice creation and orchestration through mechanisms such as over-the-top applications on User Equipment (UE) devices or network-triggered slice orchestration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If network slices are statically configured, then network infrastructure modifications are required for new services, but service rollout time increases and adaptability decreases
Solution Approach 1:
The patent implements dynamic network slicing by enabling the network to automatically create, modify, and terminate slices based on real-time conditions. The system dynamically allocates resources and configures network parameters without requiring manual infrastructure modifications, allowing services to be deployed rapidly while adapting to changing network demands.
Solution Approach 2:
The system pre-configures slice templates and resource pools that can be rapidly instantiated when needed. By preparing network resources in advance and maintaining a library of pre-approved slice configurations, the system eliminates the need for time-consuming infrastructure modifications during service rollout.
2Productivity
If network slices are dynamically created, then service rollout time decreases, but network complexity increases
Solution Approach 1:
The patent implements self-service network slicing where the system automatically manages slice creation, resource allocation, and optimization without requiring manual intervention. The network autonomously monitors conditions, adjusts resources, and provisions new slices based on predefined policies, reducing operational complexity despite increased functionality.
Solution Approach 2:
The system continuously monitors network conditions, slice performance, and resource utilization, using this feedback to automatically adjust slice configurations and resource allocation. This closed-loop control enables dynamic adaptation while maintaining manageable complexity through automated decision-making based on real-time data.
3Loss of energy
If network resources are allocated statically, then resource utilization is simplified, but resource efficiency decreases and waste increases
Solution Approach 1:
The patent implements dynamic resource allocation where network resources are continuously adjusted based on actual demand patterns. The system monitors usage metrics and automatically reallocates resources between slices, enabling efficient utilization while adapting to varying workloads and eliminating wasted capacity in static configurations.
Solution Approach 2:
The system dynamically modifies network parameters such as bandwidth allocation, resource pool sizes, and slice priorities based on real-time conditions. By continuously adjusting these parameters rather than maintaining fixed allocations, the system optimizes resource efficiency while managing complexity through automated parameter management.
Data Source
AI summary
Systems and methods described herein provide dynamic network slicing. A network device receives, from an application server, application performance requirements for an application and receives capability and performance information of an existing network slice that is servicing a User Equipment (UE) device using the application. The network device determines, based on the capability and performance information, that a new network slice is needed to support the application performance requirements for the UE device; and sends a signal to initiate a slice creation process for the new network slice.