Big Data Analytics for Large-scale Wireless Networks: Challenges and Opportunities

Hong Ning Dai*, Raymond Chi Wing Wong, Hao Wang, Zibin Zheng, Athanasios V Vasilakos

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

103 Citations (Scopus)


The wide proliferation of various wireless communication systems and wireless devices has led to the arrival of big data era in large-scale wireless networks. Big data of large-scale wireless networks has the key features of wide variety, high volume, real-time velocity, and huge value leading to the unique research challenges that are different from existing computing systems. In this article, we present a survey of the state-of-art big data analytics (BDA) approaches for large-scale wireless networks. In particular, we categorize the life cycle of BDA into four consecutive stages: Data Acquisition, Data Preprocessing, Data Storage, and Data Analytics. We then present a detailed survey of the technical solutions to the challenges in BDA for large-scale wireless networks according to each stage in the life cycle of BDA. Moreover, we discuss the open research issues and outline the future directions in this promising area.

Original languageEnglish
Article number99
Number of pages36
JournalACM Computing Surveys
Issue number5
Early online date13 Sept 2019
Publication statusPublished - Sept 2020

Scopus Subject Areas

  • Theoretical Computer Science
  • Computer Science(all)

User-Defined Keywords

  • Big data
  • Machine learning
  • Wireless networks


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