Title: Achieving Automated, Standards-Aligned Network Slicing Design and Allocation

Introduction:
Network slicing is a critical technology for the efficient operation of 5G and future 6G networks, allowing network operators to create multiple virtual networks tailored to specific service requirements. These networks, known as Network Slice Instances (NSIs) and their logical parts, Network Slice Subnet Instances (NSSIs), are designed to ensure Quality of Service (QoS) for various services such as enhanced Mobile Broadband (eMBB), massive Internet of Things (mIoT), Ultra-Reliable Low-Latency Communication (URLLC), and Vehicle-to-Everything (V2X).

The Challenge:
Currently, the design and allocation of NSIs/NSSIs are often manual processes, relying on human operators with domain knowledge and experience. This approach is time-consuming, error-prone, and unable to meet the demands of dynamically managing hundreds or even thousands of NSIs/NSSIs efficiently. The goal is to automate this process to ensure scalability, flexibility, and widespread availability of network slicing services.

Automated Design and Allocation Process:

  1. Service-Level Agreement (SLA) and Service-Level Specification (SLS) Analysis:

    • The first step is to analyze the high-level SLA/SLS requirements provided by the customer. These requirements outline the QoS expectations, including end-to-end latency, mean throughput, device count, and density.
  2. Automated Design Decision-Making:

    • Develop advanced algorithms and artificial intelligence (AI) systems to interpret the SLA/SLS requirements and translate them into detailed technical specifications for NSIs/NSSIs.
    • These systems should be capable of deciding on the structure and topology of NSI/NSSI internal building blocks, resource allocation, and deployment strategies in cloud environments.
  3. Standards Alignment:

    • Ensure that the automated design process aligns with international standards and best practices, such as those set by the 3rd Generation Partnership Project (3GPP) for 5G and future 6G networks.
    • This alignment is crucial for interoperability and compatibility across different network operators and service providers.
  4. Optimized Deployment and Configuration:

    • Use automated tools to plan the optimized deployment of NSIs/NSSIs in cloud runtime environments, considering factors such as resource availability, load balancing, and security.
    • Define operational configurations and end-to-end QoS assurance policies to meet the specified SLA/SLS requirements.
  5. Dynamic Management and Scaling:

    • Implement systems capable of dynamically managing and scaling NSIs/NSSIs in response to changing service demands and network conditions.
    • This includes the ability to create, modify, and terminate NSIs/NSSIs on-demand, ensuring flexibility and responsiveness to customer needs.
  6. Monitoring and Feedback Loop:

    • Establish a monitoring system to track the performance of NSIs/NSSIs against the SLA/SLS requirements.
    • Use feedback mechanisms to continuously improve the automated design and allocation process based on real-world performance data.

Conclusion:
Automating the design and allocation of NSIs/NSSIs is essential for the evolution of network slicing technology. By leveraging advanced algorithms, AI, and standards-aligned processes, network operators can achieve the flexibility, scalability, and efficiency required to meet the diverse and dynamic needs of modern telecommunication services. This automated approach not only enhances the quality of service but also positions network slicing as a cornerstone technology for the future of connectivity.


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