Affordable Access

Access to the full text

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

Authors
  • Medeiros, Dianne S. V.1
  • Cunha Neto, Helio N.1
  • Lopez, Martin Andreoni2
  • S. Magalhães, Luiz Claudio1
  • Fernandes, Natalia C.1
  • Vieira, Alex B.3
  • Silva, Edelberto F.3
  • F. Mattos, Diogo M.1
  • 1 Universidade Federal Fluminense - UFF, Niterói, Rio de Janeiro, Brazil , Niterói (Brazil)
  • 2 Samsung R&D Institute Brazil - SRBR, Campinas, São Paulo, Brazil , Campinas (Brazil)
  • 3 Universidade Federal de Juiz de Fora - UFJF, Juiz de Fora, Minas Gerais, Brazil , Juiz de Fora (Brazil)
Type
Published Article
Journal
Journal of Internet Services and Applications
Publisher
Springer London
Publication Date
Oct 19, 2020
Volume
11
Issue
1
Identifiers
DOI: 10.1186/s13174-020-00127-2
Source
Springer Nature
Keywords
License
Green

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.

Report this publication

Statistics

Seen <100 times