Microslice Autoconfiguration for Enterprise Wireless Networks
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Solution Overview
Problem
Current wireless communication networks, particularly CBRS networks, face challenges in efficiently configuring and managing network slices to meet the diverse service level objectives and quality of service requirements of various applications and devices within enterprise environments.
Innovation Solution
The implementation of a microslice autoconfiguration system that utilizes a remote network orchestration platform with machine learning and artificial intelligence capabilities to configure independent end-to-end logical networks tailored to specific enterprise needs, ensuring Quality of Service (QoS) and Service Level Objective (SLO) requirements are met.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual configuration of network slices is performed to meet diverse service level objectives, then service customization and QoS requirements are satisfied, but network administration complexity and time consumption increase
Solution Approach 1:
The patent segments the network into multiple independent microslices, each tailored to specific service requirements. The system divides network resources into isolated logical networks that can be independently configured and managed, allowing diverse QoS requirements to be met without increasing overall administration complexity through automated orchestration
Solution Approach 2:
The patent implements self-service through automated microslice configuration systems that automatically create, configure, and manage microslices based on service requirements. The system uses self-organizing algorithms and automated orchestration to eliminate manual configuration, allowing the network to adapt to diverse service needs without increasing administration burden
2Productivity
If automated microslice configuration is implemented using machine learning, then configuration time and administrative effort are reduced, but system complexity and initial setup requirements increase
Solution Approach 1:
The patent introduces an automated configuration system as an intermediary between network requirements and microslice implementation. This system uses machine learning algorithms and orchestration platforms to automatically translate service requirements into configured microslices, reducing configuration time while managing complexity through automated intelligence rather than manual processes
Solution Approach 2:
The patent applies parameter changes by using machine learning to dynamically adjust microslice configuration parameters based on observed network conditions and service requirements. The system learns from operational data and automatically optimizes microslice parameters, achieving fast configuration while managing complexity through data-driven automation
3Adaptability or versatility
If multiple microslices are created to serve different applications and devices, then service level objectives are met, but network resource fragmentation and management difficulty increase
Solution Approach 1:
The patent creates a universal orchestration system that manages multiple microslices through a single unified interface. The automated configuration system serves multiple functions: creating microslices, monitoring their performance, adjusting parameters, and coordinating resources across all microslices, thereby maintaining service diversity while simplifying management through multi-functionality
Data Source
AI summary
Methods and apparatus for autoconfiguring microslices in enterprise wireless communication networks using a microslice knowledgebase in a remotely located orchestration platform. Microslices are independent end-to-end logical networks operating on a shared physical infrastructure, which ensure certain Quality of Service (QoS) and Service Level Objective (SLO) requirements are met for different service types or applications. Any of the enterprise networks may be a Citizen's Broadband Radio Service (CBRS) system. A microslice knowledgebase unit in the orchestration platform configures microslices for the enterprise networks based upon communication requirements of applications, devices, and groups of devices such as service type, bandwidth requirements, using machine learning and artificial intelligence to learn communication requirements of each enterprise deployment. The microslice configuration unit in the knowledgebase may develop microslice templates based upon enterprise type, which can be used to better make recommendations to enterprise networks during initial deployment and afterwards.