Automated Cell Site Provisioning via Dependency Graph Orchestration
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Solution Overview
Problem
Existing methods for provisioning cell sites in 5G radio-access networks (RAN) are manual, time-consuming, and prone to misconfigurations, especially when dealing with a large number of sites, which hinders deployment velocity and increases operational complexity.
Innovation Solution
A management node that automates the provisioning of cell sites by converting multiple steps into a dependency graph of tasks, allowing for the execution of these tasks in an order determined by the graph, thereby streamlining the deployment process from physical infrastructure to containerized network functions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual provisioning methods are used for cell sites, then operational control and flexibility are maintained, but deployment velocity is slow and operational complexity increases
Solution Approach 1:
The system enables automated self-provisioning of cell sites through infrastructure-as-code templates and orchestration workflows that automatically configure physical infrastructure, container platforms, and network functions without manual intervention, allowing the system to provision itself at scale
Solution Approach 2:
The provisioning process is segmented into distinct automated stages including physical infrastructure provisioning, container platform deployment, and network function instantiation, with each stage managed by separate orchestration workflows that can be executed independently and in parallel
2Loss of time
If manual provisioning methods are used for cell sites, then configuration accuracy can be controlled, but time consumption increases significantly
Solution Approach 1:
Configuration templates and infrastructure-as-code definitions are prepared in advance with all necessary parameters and dependencies defined, allowing automated instantiation and elimination of manual configuration steps during deployment
Solution Approach 2:
The orchestration system implements automated validation, error detection, and corrective workflows that monitor provisioning progress and configuration accuracy in real-time, providing feedback loops to ensure correct deployment without manual verification
3Productivity
If automated provisioning is implemented, then deployment velocity improves, but system complexity increases
Solution Approach 1:
A universal orchestration platform is deployed that can provision multiple types of cell sites and network functions using standardized infrastructure-as-code templates and workflows, reducing the need for site-specific customization and simplifying management across diverse deployments
4Reliability
If large numbers of cell sites are provisioned manually, then error rates increase, but automation infrastructure complexity increases
Solution Approach 1:
The system implements automated self-validation and self-correction mechanisms where provisioning templates include built-in validation rules and the orchestration system automatically detects and corrects configuration errors without human intervention
Solution Approach 2:
Proven configuration templates and orchestration workflows are replicated across multiple cell sites, ensuring consistent and error-free provisioning by copying validated configurations rather than creating new configurations manually for each site
Data Source
AI summary
In an example, a method for provisioning a cell site in a 5G RAN may include receiving a plurality of steps involved in provisioning the cell site for the 5G RAN. In an example, provisioning the cell site may include provisioning of a physical infrastructure layer, a container orchestration platform on the physical infrastructure layer, and a containerized network function (CNF) instance associated with the 5G RAN in the container orchestration platform. Further, the method may include converting the plurality of steps into a dependency graph of tasks. The dependency graph may represent workflows and relationships between the tasks. Furthermore, based on feeding the dependency graph as an input to an orchestrator, the method may include provisioning the cell site by executing the tasks in an order according to the dependency graph.