# An Overview of Machine Learning and 5G for People with Disabilities
## 6 A 5G Network Slicing Architecture for People with Disabilities
### Benefits of a Network Slicing Architecture for People with Disabilities  
Next, we introduce the main benefits of the network slicing architecture for people with disabilities:  
Network slicing improves the Quality of Service (QoS) of the different applications for people with disabilities allocating dedicated slices for each use case. The 5G use cases can be clustered into three major categories (as discussed in Section 3.6): eMBB, mMTC, and URLLC. In the ecosystem of people with disabilities, the different applications have been classified as one of the three different types of slices depending on their specific requirements (see Section 6.1): low latency, low loss rate, high reliability, etc. For instance, mMTC applications such as sensors, actuators (home appliances), and wearables for the disabled at home (see Section 6.1) typically have a multitude of low throughput devices, whereas navigation systems for the visually impaired or remote driving in the URLLC category require extremely low latency and very high reliability. In addition, remote healthcare for the disabled in eMBB category requires very high bandwidth to transmit a large amount of content.  
The traditional mobile communication networks that provide services based on the \"one-size-fits-all\" design are usually built on specialized equipment and dedicated platforms with weak flexibility and scalability. Therefore, they cannot address the wider range of performance and cost requirements of the new use cases for people with disabilities.  
On the other hand, 5G network slices, which are represented by logically isolated and self-contained networks, are flexible enough and highly customizable to accommodate diverse use cases, simultaneously, over the same network infrastructure [71]. It is possible to provide network services efficiently when the large monolithic network functions of the traditional networks, based on specific hardware, are decomposed into several software, based smaller modular network functionalities with varying granularity [71]. These 5G network functions can be combined appropriately with a suitable 5G RAT on demand to form different network slices that are tailored to specific use cases.  
Existing QoS architectures like Differentiated Services (DiffServ) [72] can discriminate different types of traffic (e.g., VoIP traffic, high-definition video, web browsing, etc.), but they can't discriminate and treat the same traffic (e.g., VoIP traffic) coming from different tenants in a different way. In contrast, network slicing provides an end-to-end virtual network for a given tenant.  
Furthermore, network slicing can improve the scalability of the network as service requirements and the number of users change. The amount of traffic that flows through the network is not always the same. IoT devices for people with disabilities (wearables, cameras, etc.) operate in sleep and wake cycles, which causes network resources to be idle or over-utilized sometimes. Network slicing enables the dynamic allocation of idle network resources of a particular network slice to another slice that demands high resource requirements. Dynamic resource allocation enables the accomplishment of the QoS requirements even during congestion situations. This technique improves the efficiency of resource utilization and enhances the network performance. Finally, network slicing improves reliability, security and privacy, since it isolates the network resources of one service from the others. Reliability is improved because faults or errors in one slice don't affect the proper functioning of the rest. Slice isolation ensures that the security attack on one slice doesn't affect the others. Allocating separate slices for different applications with strong slice isolation mechanisms allows better protection of sensitive information from the disabled.