Last updated on Feb 7, 2024

What are the benefits and challenges of using virtual machines for network slicing in 5G networks?

Network slicing is a key feature of 5G networks that allows operators to create multiple virtual networks on the same physical infrastructure, each with different performance, security, and service characteristics. Virtual machines (VMs) are one of the technologies that enable network slicing by virtualizing network functions and running them on shared hardware resources. In this article, we will explore the benefits and challenges of using VMs for network slicing in 5G networks.

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1 Benefits of VMs for network slicing

VMs offer several advantages for network slicing, such as flexibility, scalability, isolation, and cost-efficiency. VMs can be dynamically created, configured, and deleted according to the network slice requirements, allowing operators to optimize the resource utilization and service delivery. VMs also provide a high degree of isolation between different network slices, ensuring that each slice has its own operating system, security policies, and performance guarantees. Moreover, VMs can reduce the capital and operational expenses of network slicing by enabling the consolidation of multiple network functions on fewer physical servers, thus saving space, power, and cooling costs.

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Karthikeyan R.

DC Manager - STT Global Data Centres India Private Limited | EXIN EPI CDCP® | ETAP | Load flow | Harmonic Analysis
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Network slicing offers a dynamic way to carve up a physical network into multiple virtual networks, each tailored to specific needs. Virtual machines (VMs) play a crucial role in enabling this slicing, offering several key benefits: Flexibility: Dynamic creation and deletion: VMs can be quickly spun up or shut down based on changing resource demands within each slice, ensuring efficient resource utilization. Customization: Each VM can be configured with the specific operating system, software, and security policies required by the corresponding slice, providing unparalleled agility. Scalability: Horizontal scaling: Adding new VMs within a slice scales up resources horizontally to meet growing demands without impacting other slices.

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2 Challenges of VMs for network slicing

However, VMs also pose some challenges for network slicing, such as complexity, overhead, and compatibility. VMs require a hypervisor layer to manage the virtualization of the hardware resources, which adds complexity and overhead to the network slicing process. VMs also introduce additional latency and jitter to the network functions, which may affect the quality of service and user experience of some latency-sensitive applications, such as augmented reality or online gaming. Furthermore, VMs may not be compatible with some legacy or proprietary network functions that require specific hardware or software configurations, limiting the interoperability and flexibility of network slicing.

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Karthikeyan R.

DC Manager - STT Global Data Centres India Private Limited | EXIN EPI CDCP® | ETAP | Load flow | Harmonic Analysis
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While VMs offer several benefits for network slicing, they also come with some key challenges that need to be considered: Complexity: Additional layers: Introducing a VM layer adds complexity to the network architecture, increasing management overhead and potential points of failure. Resource overhead: VMs themselves consume resources, reducing the overall available resources for network functions within the slice. Troubleshooting: VM-related issues can complicate troubleshooting network slice problems, adding time and effort to problem-solving.

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3 Alternatives to VMs for network slicing

Besides VMs, there are other technologies that can be used for network slicing, such as containers and serverless computing. Containers are lightweight and portable software units that package the network functions and their dependencies, without requiring a separate operating system or hypervisor. Containers can improve the performance, scalability, and portability of network slicing, but they may also compromise the security and isolation of different network slices, as they share the same kernel and resources. Serverless computing is a cloud-based model that allows operators to run network functions on demand, without provisioning or managing any servers. Serverless computing can simplify and accelerate the network slicing process, but it may also incur higher costs, lower reliability, and less control over the network functions.

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4 Best practices for using VMs for network slicing

To make the most of using VMs for network slicing, operators should consider some best practices, such as selecting the right hypervisor and VM type, optimizing resource allocation and scheduling, implementing monitoring and management tools, and adopting open standards and interfaces. This will help minimize overhead and latency, ensure availability, reliability, and quality of service of each network slice, as well as guarantee interoperability and compatibility of VMs with different network functions and vendors.

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Karthikeyan R.

DC Manager - STT Global Data Centres India Private Limited | EXIN EPI CDCP® | ETAP | Load flow | Harmonic Analysis
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While VMs offer immense potential for network slicing, navigating their challenges requires careful planning and strategic implementation. Here are some best practices to maximize the benefits and minimize the drawbacks: Planning and Design: Clearly define slice requirements: Understand the specific needs of each slice regarding bandwidth, latency, security, and scalability before introducing VMs. Choose the right VM technology: Evaluate different VM solutions based on performance, security features, management tools, and compatibility with your infrastructure. Design for isolation and security: Implement strong network segmentation, proper access controls, and robust VM security configurations within each slice.

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5 Future trends of VMs for network slicing

As 5G networks evolve and require more diverse and dynamic network slices, VMs will remain an essential element. However, VMs must also adapt to meet the new challenges and opportunities of network slicing. This includes integrating with other virtualization technologies such as containers and serverless computing to form hybrid and flexible network slices, leveraging AI and ML to automate and optimize the creation, configuration, and management of VMs for network slicing, supporting edge computing and multi-cloud scenarios for distributed and heterogeneous network slices, as well as enhancing the security and privacy of VMs to protect the data and services of each network slice.

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