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Big Data Analytics for Large-scale Wireless Networks: Challenges and Opportunities
Faculty of Information Technology, Macau University of Science and Technology, Avenida Wai Long, Taipa, Macau.
Department of Computer Science and Engineering, Hong Kong University of Science and Technology (HKUST), Clear Water Bay, Kowloon, Hong Kong.
Norwegian University of Science and Technology, Norway.
School of Data and Computer Science, Sun Yat-sen University, Xiaoguwei Island, Guangzhou, China.
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2019 (engelsk)Inngår i: ACM Computing Surveys, ISSN 0360-0300, E-ISSN 1557-7341, Vol. 52, nr 5, artikkel-id 99Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

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.

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ACM Digital Library, 2019. Vol. 52, nr 5, artikkel-id 99
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URN: urn:nbn:se:ltu:diva-76203DOI: 10.1145/3337065ISI: 000496755500013Scopus ID: 2-s2.0-85072409619OAI: oai:DiVA.org:ltu-76203DiVA, id: diva2:1356835
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Validerad;2019;Nivå 2;2019-10-02 (johcin)

Tilgjengelig fra: 2019-10-02 Laget: 2019-10-02 Sist oppdatert: 2019-12-09bibliografisk kontrollert

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