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A survey on data analysis on large-Scale wireless networks: online stream processing, trends, and challenges

2020; Springer Science+Business Media; Volume: 11; Issue: 1 Linguagem: Inglês

10.1186/s13174-020-00127-2

1869-0238

Dianne S. V. Medeiros, Helio N. Cunha Neto, Martin Andreoni Lopez, Luiz Magalhães, Natália C. Fernandes, Alex Borges Vieira, Edelberto Franco Silva, Diogo M. F. Mattos,

Anomaly Detection Techniques and Applications

Abstract In this paper we focus on knowledge extraction from large-scale wireless networks through stream processing. We present the primary methods for sampling, data collection, and monitoring of wireless networks and we characterize knowledge extraction as a machine learning problem on big data stream processing. We show the main trends in big data stream processing frameworks. Additionally, we explore the data preprocessing, feature engineering, and the machine learning algorithms applied to the scenario of wireless network analytics. We address challenges and present research projects in wireless network monitoring and stream processing. Finally, future perspectives, such as deep learning and reinforcement learning in stream processing, are anticipated.