大规模无线网络数据分析研究:在线流处理、趋势和挑战

IF 2.4 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS
Dianne S. V. Medeiros, H. N. C. Neto, Martin Andreoni Lopez, Luiz Claudio S. Magalhães, N. Fernandes, A. Vieira, E. F. Silva, D. M. F. Mattos
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引用次数: 22

摘要

本文主要研究了基于流处理的大规模无线网络知识提取。我们提出了无线网络采样、数据收集和监测的主要方法,并将知识提取描述为大数据流处理中的机器学习问题。我们展示了大数据流处理框架的主要趋势。此外,我们还探讨了应用于无线网络分析场景的数据预处理、特征工程和机器学习算法。我们提出了无线网络监测和流处理方面的挑战和研究项目。最后,展望了流处理中的深度学习和强化学习等未来前景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A survey on data analysis on large-Scale wireless networks: online stream processing, trends, and challenges
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.
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来源期刊
Journal of Internet Services and Applications
Journal of Internet Services and Applications COMPUTER SCIENCE, INFORMATION SYSTEMS-
CiteScore
3.70
自引率
0.00%
发文量
2
审稿时长
13 weeks
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