Abstract
A surge in Artificial Intelligence (AI) services and applications has been spurred by advances in deep learning. Massive data generation at the network edge is being sparked by the fast advancements in mobile computing and Artificial Intelligence of Things (AIoT). Big data can only be completely realized if the AI frontiers are pushed to the network edge, propelled by the successes of AI and IoT. It is hoped that Edge Computing would help to fulfil this trend by supporting AI applications that are computationally heavy on edge devices. Machine learning algorithms may be deployed to the end devices in which the data is created thanks to Edge AI. For every individual and business, Edge Intelligence has the ability to give AI at any moment, any place. This paper is limited to evaluating the definitions, history and applications of Software Defined Networks (SDNs), Network Functions Virtualization (NFV), Edge Computing (EC), Artificial Intelligence (AI)/Machine Learning (ML) techniques.
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