I. Introduction
The development of artificial intelligence is blooming at a never-before-seen rate (AI). Supervised learning, the far more fascinating area of artificial intelligence, must have made substantial progress in a multitude of areas, from feature extraction, speech recognition, & computational linguistics to chess gameplay, for example, AlphaGo, robotic systems, and a plethora of areas. These advances have been driven by significant innovations in methodology, computational power, & big data. As a result of such innovations, a range of intelligent applications such as intelligent virtual assistants, customized shopping suggestions, video monitoring, or smart home appliances has shot to fame and become wildly popular. Edge computing essentially moves cloud services from the core of the network to the network edges which are closer to IoT gadgets and data sources, has recently been proposed. As illustrated below, an edge node could be a network gateway, a server tied toward an internet connection such as WiFi, network, or central node, a local end-device that could link to it through device-to-device (D2D) communications, such as a microdata center that seems to be accessible to neighboring devices. One of the most interesting components accentuated by edge computing is physical closeness towards digital resources [1].