ABSTRACT
As a result of development of a network of interconnected device's applications, interconnected Cloud Computing (CC) confronts several risks such as scalability, safety, delay, and network problems. Fog Computing has emerged as a new technology, these challenges will be overcome by bringing Cloud Computing closer to the Internet of Vehicles (IoV). Providing information produced by Internet-Connected devices at the edge is the fundamental feature of the fog. Instead of sending data to a cloud server, the fog node processes and stores it locally. Unlike the cloud, Fog Computing provides high-quality services quickly. The Internet of Things can provide a reliable and secure service to multiple IoV customers via Fog Computing. This way, services and resources can be handled closer to devices, at the network edge. In contrast to popular belief, Fog computing is not an alternative for computing in the cloud, and vice versa. It is still possible to link to a cloud-based data center for further processing even when data has been processed at the periphery. To summarize, we present layout, security Fog Computing via Machine Learning, proposed optimization algorithm of Fog Computing in Machine Learning.
