Mobile Big Data: The Fuel for Data-Driven Wireless

Xiang Cheng, Luoyang Fang, Liuqing Yang, Shuguang Cui

Research output: Contribution to journalArticle

30 Scopus citations

Abstract

In the past decade, the smart phone evolution has accelerated the proliferation of the mobile Internet and spurred a new wave of mobile applications, leading to an unprecedented mobile data volume generated from the mobile devices, content servers, and network operators, which are mainly nonstructured. In this big data era, such nonstructured data fragments are pieced together such that, drastically differing from the traditional practice where services determine and define the data, data is becoming a proactive entity that may drive and even create new services. Compared with the so-termed 5V characteristics of generic big data, namely volume, variety, velocity, veracity, and value, mobile big data is distinct in its unique multidimensional, personalized, multisensory, and real-time features. In this survey, we provide in-depth and comprehensive coverage on the features, sources and applications of mobile big data, as well as the current state-of-the-art, challenges and opportunities for research and development in this field, with an emphasis on the user modeling, infrastructure supporting, data management, and knowledge discovery aspects.

Original languageEnglish (US)
Article number7945539
Pages (from-to)1489-1516
Number of pages28
JournalIEEE Internet of Things Journal
Volume4
Issue number5
DOIs
StatePublished - Oct 2017
Externally publishedYes

Keywords

  • Big data applications
  • data analysis
  • data mining
  • mobile communication
  • mobile computing
  • mobile learning
  • pervasive computing

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