# An Overview of Machine Learning and 5G for People with Disabilities
## 6 A 5G Network Slicing Architecture for People with Disabilities  
Additionally, 5G can offer a wide range of network services with different performance requirements. A network slicing architecture allows network operators to support heterogeneous services. Network slicing consists of dividing the physical network into multiple logical networks (network slices); each logical network is optimized to provide the required network capabilities for a specific application/service. Network slicing opens new business opportunities for mobile operators, since they are able to split their physical network resources into multiple logical slices and lease these slices out to interested parties. Network slicing divides the physical network into multiple virtualized logically isolated end-to-end networks. A '5G slice' is composed of a collection of 5G NFs and specific RAT settings that are combined for a specific use case. A 5G slice can span all domains of the network: access network, transport network, core network, and terminal domains [59]. Network slicing services can be automatically generated, maintained, or terminated according to services' requirements. Therefore, network slicing is a flexible and scalable solution when the same operator network needs to accommodate different use cases, each with its own service requirements. For this reason, it has attracted the attention of academia and industry alike. Network operators can also deploy, flexibly and quickly a wide range of services for applications that target people with disabilities using network slicing. Next, we introduce the main design elements of our devised 5G network slicing architecture for people with disabilities (see Figure 6). _Infrastructure layer_: it refers to the physical network infrastructure, which includes the RAN, the edge cloud, the wide area transport network, and the core network. It provides the control and management of the infrastructure, and allocates resources (computing, storage, bandwidth, etc.) to network slices so that the higher layers can access and handle them appropriately. Since slices may span multiple domains, this layer comprises the infrastructure of multiple operators [60]. _Network function layer_: it executes all the operations to manage the virtual resources and the life cycle of the network functions. It enables the optimal assignment of the virtual resources to the network slices, and chains multiple slices together to provide a specific service or application [61]. Two fundamental technological enablers of this layer are virtualization of network functions (Network Function Virtualization, NFV) [62], as well as software-defined, programmable network functions (Software Defined Networking, SDN) [63]. NFV is a technology used to virtualize complex hardware-based network node functions into software building blocks that can be connected and chained to create advanced communication services; these flexible software blocks are called VNFs (Virtualized Network Functions). SDN (Software-Defined Networking) technology is an approach to network management that decouples the network control, data forwarding paths, and functions. This way, the SDN architecture enables the network control to become directly programmable and the underlying infrastructure is abstracted from applications and network services. _Service layer_: The service layer represents the services (end-user or business services) to be supported. Each service is represented by a service instance and is provided by a network operator or a third party. A Network Slice Instance (NSI) is a managed entity  
Figure 6: Network slicing architecture for people with disabilities. created by an operator's network with a lifecycle independent of the lifecycle of the service instance(s) [64]. An NSI provides the network characteristics (e.g., ultra-low-latency, ultra-reliability) required by a service instance. An NSI may also be shared across multiple service instances provided by the network operator.