Description: Edge scalability refers to the ability of edge computing systems to handle increasing workloads or be expanded to accommodate that growth. This concept is fundamental in the context of edge inference, where devices process data locally rather than relying on centralized servers. Scalability allows these systems to adapt to rising demand, either by adding more devices to the network or by enhancing the processing capacity of existing devices. Key characteristics of edge scalability include the flexibility to integrate new devices, the ability to efficiently distribute workloads, and the possibility of updating software and hardware without interrupting service. This capability is especially relevant in applications requiring real-time processing, such as artificial intelligence, the Internet of Things (IoT), and industrial automation, where latency and efficiency are critical. In summary, edge scalability is an essential component to ensure that edge inference systems can evolve and adapt to the changing needs of users and a variety of applications.
