Cloud-Native Network Slicing With Topology-Reprogrammable CI/CD Testing
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Solution Overview
Problem
Traditional network topology design and Test-as-a-Service (TaaS) processes are separated, leading to scalability challenges, high costs, and inefficiencies in implementing continuous integration and continuous delivery (CI/CD) for Cloud-Native Networks (CNNs), especially in hybrid cloud environments, due to fixed IP address schemes and differences between lab and field topologies.
Innovation Solution
A topology-reprogrammable test environment using a 3D IP address scheme and a TaaS orchestrator to manage network slicing and CI/CD, enabling flexible network testing by cloning NCs with CDTs that emulate CNFs, allowing for scalable and cost-effective deployment of TaaS across various network environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional separated processes are used for network topology design and TaaS, then existing network IP address schemes can be maintained, but scalability and deployment efficiency deteriorate
Solution Approach 1:
The patent merges network topology design and TaaS into a unified integrated process. The TaaS orchestrator is embedded within the network topology design process, allowing test agents to be automatically deployed as part of network setup. This integration eliminates the need for separate TaaS deployment processes and enables scalable testing across diverse network topologies without increasing operational complexity.
Solution Approach 2:
The patent creates a universal TaaS orchestrator that can manage multiple network topologies and test scenarios through a single unified system. The orchestrator supports various network configurations (lab and field topologies) and can deploy test agents across different environments, making the TaaS system adaptable to diverse network architectures without requiring topology-specific deployment processes.
2Adaptability or versatility
If fixed network IP address schemes are used, then network infrastructure can be maintained, but flexibility in topology reconfiguration deteriorates
Solution Approach 1:
The patent implements dynamic IP address assignment within the 3D IP address scheme, allowing IP addresses to be automatically allocated and reconfigured based on current network topology requirements. The TaaS orchestrator dynamically manages IP assignments for test agents and network functions, enabling flexible topology reconfiguration without manual IP management. This dynamic approach maintains deployment ease while providing topology flexibility.
3Reliability
If lab testing is performed with fixed topologies, then testing processes can be simplified, but field deployment reliability deteriorates
Solution Approach 1:
The patent uses digital twins to create virtual copies of field network topologies in the lab environment. The TaaS orchestrator clones field topology configurations and deploys test agents in replicated virtual environments, allowing lab testing to mirror actual field conditions. This copying approach enables reliable field validation while keeping lab testing processes manageable through automated topology replication.
Solution Approach 2:
The patent changes testing parameters by implementing topology-aware test case selection and execution. The TaaS orchestrator adapts test parameters based on detected network topology characteristics, automatically adjusting test scenarios to match field conditions. This parameter adaptation ensures field reliability while maintaining simplified testing processes through automated topology-aware test configuration.
4Reliability
If comprehensive TaaS testing is implemented, then validation thoroughness can be improved, but implementation cost increases
Solution Approach 1:
The patent implements self-service testing where the TaaS orchestrator automatically selects, configures, and executes appropriate test cases based on the detected network topology. The system autonomously determines which validation scenarios are needed and executes them without manual intervention, reducing implementation costs while maintaining thorough validation through automated topology-aware test selection.
Data Source
AI summary
A topology-reprogrammable test environment is provided that can support the needs of CI/CD/CV in the field. The system disclosed provides a highly scalable network architecture to simplify the implementation of network slicing, TaaS and network CI/CD, and solves problems related to the complexity of cloud-native network (CNN) deployments. A Network Cell (NC), comprises or consists of a Containerized Network Function (CNF), a Containerized Digital Twin (CDT), and a Containerized Test Agent (CTA). The CDT has at least two personalities, e.g., an emulator of the CNF in the same NC or a nodal of the CNF. The choice of personality of the CDT is controlled by the CTA of the NC. A number of NCs use a 3D IP address to interconnect and form a new kind of CNN over the infrastructure of VRs.