Analysis of Machine Learning Algorithms for Efficient Cloud and Edge Computing in the IoT

Abstract

The internet of things (IoT) technology, which connects internet-connected devices, continues to extend the current internet by allowing communication and interactions across the physical and cyber worlds. The IoT generates big data that is characterized by its velocity in terms of time and place dependency, with a diversity of diverse modalities and fluctuating data quality, in addition to increased volume. The key to designing smart IoT applications is intelligent data processing and analysis. This chapter first describes the details of how cloud services and edge technology work and support the internet of things with many challenges and limitations in the overall internet services. Second, it describes the support of different machine learning algorithms (MLA) in the different fields of internet of things applications. Finally, there is a description of the future research scopes and open issues in the field of the internet of things with machine learning algorithms for further research work initiation.