The Emerging Role of the knowledge Driven Applications of Wireless Networks for Next Generation online Stream Processing

Stream processing is used to collect information from large-scale wireless networks, which is the subject of the current article. We describe the basic techniques for sample selection, information gathering, and network surveillance in wireless networks, as well as how understanding extracting may be thought of as a ML challenge on large data stream processing systems. We demonstrate the most important developments in big data stream processing technologies in this paper. Furthermore, we investigate the information preparation, extraction of features, and machine learning methods that may be implemented to the case of wireless network analytics in more detail. We talk about difficulties and academic research in wireless network surveillance & stream analysis, as well as their outcomes. Furthermore, different innovations in stream processing, including such deep learning or reinforcement learning, are expected to be explored further.