Cluster Node Configuration for Scalable Core Network Functions
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Solution Overview
Problem
Existing technologies face challenges in dynamically expanding or reducing network coverage and processing capacity while minimizing dependency on data centers or telecommunications equipment rooms, and there is a need for improved methods to leverage Kubernetes for network function deployment.
Innovation Solution
A configuration method and unit that dynamically adjust the number of nodes in a cluster by selecting and deploying network functions using a configuration unit with AI-driven algorithms to optimize node selection and resource allocation, reducing dependency on data centers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the total number of nodes in a cluster is increased to expand network coverage or processing capacity, then the network capacity is improved, but the dependency on data centers or telecommunications/equipment rooms increases
Solution Approach 1:
The patent segments the network function deployment from centralized data centers to distributed edge nodes. By dividing the network into multiple independent nodes that can be deployed across different locations (edge devices, gateways, or cloud environments), the system achieves network expansion without proportionally increasing dependency on centralized data centers. Each node operates semi-independently, allowing the network to scale horizontally while maintaining distributed architecture.
Solution Approach 2:
The patent transitions the deployment dimension from traditional centralized data center locations to multi-dimensional edge locations. Nodes can be deployed at network edges, user premises, mobile devices, or cloud platforms, adding spatial and architectural dimensions to network deployment. This dimensional expansion allows network capacity to grow without linearly increasing data center dependency.
2Adaptability or versatility
If traditional network services are virtualized using NFV, then service flexibility is improved, but the complexity of managing and orchestrating network functions increases
Solution Approach 1:
The patent creates a universal node architecture that can deploy multiple network functions across different node types and locations. The same orchestration mechanisms work uniformly whether deploying functions at edge devices, gateways, or cloud platforms. This universal approach simplifies management by providing consistent interfaces and procedures, reducing orchestration complexity despite the diversity of deployment environments.
Solution Approach 2:
The patent implements dynamic orchestration that automatically adapts to changing network conditions, node availability, and service requirements. The system dynamically selects which nodes to deploy functions on, automatically scales node capacity, and reconfigures service chains in real-time. This dynamic automation reduces the manual orchestration burden while maintaining high service flexibility.
3Adaptability or versatility
If nodes are dynamically added or removed from a cluster, then network scalability is improved, but the configuration and management complexity increases
Solution Approach 1:
The patent implements self-service mechanisms where nodes automatically register with the orchestration system upon joining the cluster and automatically deregister when leaving. The orchestration system automatically detects node changes, recalculates optimal function placements, and redistributes workloads without manual intervention. This self-service automation eliminates complex manual configuration steps while enabling dynamic node addition and removal.
Solution Approach 2:
The patent establishes continuous feedback loops between nodes and the orchestration system. Nodes report their status, capacity, and health metrics to the orchestrator, which uses this feedback to make real-time decisions about function deployment and node management. When nodes are added or removed, the feedback mechanism triggers automatic reconfiguration, simplifying the management of dynamic cluster changes.
Data Source
AI summary
A configuration method and a configuration unit are provided. The configuration method is for a configuration unit coupled to a cluster. The configuration method includes calculating a first node number at a first time instant, and selecting at least one first node corresponding to the first node number from at least one node of the cluster. The at least one first node is configured to run a plurality of network functions of a core network respectively. The coverage or processing capacity of the network of the cluster can be expanded or reduced by increasing or decreasing the total node number of the at least one node in the cluster. The dependence on data centers or telecommunication rooms can be reduced.